DESC:SYSTEM TO ENHANCE CYBERSECURITY DURING CHARGING OF AN ELECTRIC VEHICLE
CROSS REFERENCE TO RELATED APPLICTIONS
The present application claims priority from Indian Provisional Patent Application No. 202421026809 filed on 31/03/2024, the entirety of which is incorporated herein by a reference.
TECHNICAL FIELD
The present disclosure generally relates to cybersecurity in electric vehicle charging. Further, the present disclosure particularly relates to enhancing cybersecurity during charging of a battery of an electric vehicle at a charging station.
BACKGROUND
Electric vehicles have gained widespread adoption due to benefits for example reduced dependency on fossil fuels and lower emissions. Further, electric vehicles rely on battery technique for energy storage, requiring periodic charging at dedicated charging stations. Moreover, communication between an electric vehicle and a charging station is important for managing power transfer, assuring safe operation, and enabling billing transactions. Various charging standards, comprising Combined Charging System (CCS) and CHAdeMO, enable communication protocols for data exchange between an electric vehicle and a charging station. However, such communication introduces cybersecurity risks which may compromise integrity of charging sessions and data security.
Further, conventional cybersecurity measures applied in charging infrastructures primarily involve authentication mechanisms to verify legitimacy of a charging station before initiating a charging session. Password-based authentication and Public Key Infrastructure (PKI)-based authentication have been commonly employed to validate credentials of a charging station. However, reliance on authentication alone presents security vulnerabilities. Cyber-attacks for example credential theft, man-in-the-middle attacks, and spoofing of a legitimate charging station compromise security, resulting in unauthorized access to an electric vehicle control system. Moreover, conventional authentication techniques fail to monitor integrity of software operating within an electric vehicle control system during a charging session, leaving the system vulnerable to malware injection or firmware tampering.
Additionally, intrusion detection systems have been employed to detect cybersecurity threats within electric vehicle networks. Further, conventional intrusion detection systems analyze network traffic patterns, detect anomalies, and generate alerts upon identification of suspicious activities. However, reliance on network-based anomaly detection alone proves insufficient due to dynamic network behavior and presence of encrypted communication channels. Further, such techniques often produce false positives, leading to unnecessary disruptions during charging sessions. Moreover, network-based security measures fail to directly verify integrity of software stored within an electric vehicle control system, leaving security gaps.
Furthermore, cryptographic hash functions have been utilized to verify software integrity in computing environments. Hash functions generate unique hash values based on content of software, enabling comparison against a reference hash value stored in a secure repository. However, conventional hash-based integrity verification techniques often rely on manual validation or scheduled verification cycles, failing to provide real-time detection of software compromise. Further, absence of automated verification mechanisms increases risk of delayed response to cyber threats, allowing malware to persist undetected within an electric vehicle control system.
Moreover, cybersecurity threats affecting charging stations pose risks beyond a single electric vehicle. Compromised charging stations serve as attack vectors capable of spreading malware to multiple electric vehicles using the same charging infrastructure. Further, conventional cybersecurity approaches lack mechanisms to trace cybersecurity breaches back to a specific charging station, making difficult to isolate compromised infrastructure and prevent further spread of cyber threats. Additionally, lack of cybersecurity awareness among electric vehicle users exacerbates risks, as users remain unaware of threats affecting charging stations.
In light of the above discussion, there exists an urgent need for solutions that overcome cybersecurity risks associated with conventional systems and techniques for enhancing cybersecurity during charging of a battery of an electric vehicle at a charging station.
SUMMARY
The aim of the present disclosure is to enhance cybersecurity during charging of a battery of an electric vehicle at a charging station. The system of the present disclosure aims to prevent cyber-attacks targeting software integrity of an electric vehicle control unit during a charging operation by validating authenticity of software in real-time. Further, the present disclosure aims to enable identification of compromised charging stations to prevent further cybersecurity breaches across a fleet of electric vehicles.
In an aspect, the present disclosure provides a system to enhance cybersecurity during charging of a battery of an electric vehicle at a charging station. A control unit positioned within the electric vehicle exchanges data with the charging station through a communication interface during a charging operation. A security verification unit monitors integrity of software stored within the control unit by detecting potential cyber-attacks occurring during the charging operation. A hash value computation unit generates a current hash value corresponding to the software and forwards the generated current hash value for validation. A data reception unit acquires a predetermined hash value from a remotely located data repository, wherein the predetermined hash value represents a reference for integrity verification. A comparison unit determines software compromise through a hash value comparison. A warning generation unit processes results from the comparison unit and issues an alert upon detecting a cyber-attack. A display interface renders a visual indicator on a digital map marking the identified charging station on display screens of the fleet of electric vehicles.
Further, the security verification unit employs a cryptographic verification technique for detecting software compromise, wherein an asymmetric encryption technique is applied for authentication of the software. Further, the hash value computation unit applies a secure hashing function to generate the current hash value, wherein the secure hashing function is selected from a set consisting of SHA-256, SHA-3, and Blake2. The comparison unit stores a historical record of hash value comparisons to facilitate forensic analysis of cyber-attacks, wherein the historical record is encrypted and stored within a secure data repository.
Furthermore, the system comprises a certificate validation unit to verify validity of a software certificate associated with the charging station and a connection control unit to enable a data connection to the charging station only if the software certificate is valid. Further, a certificate management unit revokes a currently valid software certificate of the charging station upon detection of a cyber-attack. The warning generation unit categorizes the detected cyber-attack based on severity levels before issuance of the alert, wherein the severity levels are determined based on a predefined risk assessment matrix.
Additionally, the display interface updates the digital map to indicate a real-time cybersecurity status of multiple charging stations, wherein a color-coded scheme differentiates charging stations based on cybersecurity risk levels. Further, the warning generation unit transmits the alert to a fleet management server in addition to the fleet of electric vehicles, wherein the fleet management server logs cyber-attack incidents and generates analytical reports for cybersecurity monitoring. The security verification unit performs periodic integrity checks of software beyond the charging operation, wherein such periodic integrity checks are scheduled based on a predefined time interval or triggered by anomaly detection mechanisms.
In another aspect, the present disclosure provides a method to enhance cybersecurity during charging of a battery of an electric vehicle at a charging station. A control unit positioned within the electric vehicle receives data from the charging station through a communication interface during a charging operation. A security verification unit monitors integrity of software stored within the control unit by detecting potential cyber-attacks occurring during the charging operation. A hash value computation unit generates a current hash value corresponding to the software and forwards the generated current hash value for validation. A data reception unit acquires a predetermined hash value from a remotely located data repository, wherein the predetermined hash value represents a reference for integrity verification. A comparison unit compares the current hash value with the predetermined hash value to determine whether the software is compromised. A warning generation unit processes results from the comparison unit and issues an alert upon detecting a cyber-attack. A display interface renders a visual indicator on a digital map marking the charging station involved in the cyber-attack, wherein the digital map is presented on display screens of a fleet of electric vehicles.
Further, a multi-factor validation process is performed by the security verification unit, wherein integrity verification of both control unit firmware and external communication logs associated with the control unit is executed. Further, the alert generated by the warning generation unit comprises a geofencing mechanism restricting access to the charging station by disabling charging authorization for battery-electric vehicles within a predefined proximity of the charging station. An artificial intelligence-based anomaly detection mechanism is utilized by the security verification unit to predict potential cyber-attacks before software compromise occurs based on deviations in charging station communication patterns. Furthermore, the warning generation unit transmits the alert through a decentralized blockchain-based cybersecurity framework to prevent tampering and unauthorized modification of alert data.
BRIEF DESCRIPTION OF DRAWINGS
The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.
Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:
FIG. 1 illustrates a system 100 to enhance cybersecurity during charging of a battery of an electric vehicle at a charging station, in accordance with embodiments of the present disclosure;
FIG. 2 illustrates a method 200 to enhance cybersecurity during charging of the battery of the electric vehicle at the charging station, in accordance with embodiments of the present disclosure;
FIG. 3 illustrates a hash computation and comparison process diagram, in accordance with embodiments of the present disclosure; and
FIG. 4 illustrates a digital map interface diagram, in accordance with embodiments of the present disclosure.
In the accompanying drawings, an underlined number is employed to represent an item over which the underlined number is positioned or an item to which the underlined number is adjacent. A non-underlined number relates to an item identified by a line linking the non-underlined number to the item. When a number is non-underlined and accompanied by an associated arrow, the non-underlined number is used to identify a general item at which the arrow is pointing.
DETAILED DESCRIPTION
The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognise that other embodiments for carrying out or practising the present disclosure are also possible.
The description set forth below in connection with the appended drawings is intended as a description of certain embodiments of a system to enhance cybersecurity during charging of a battery of an electric vehicle at a charging station and is not intended to represent the only forms that may be developed or utilised. The description sets forth the various structures and/or functions in connection with the illustrated embodiments; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimised to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention.
While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however, that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.
In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings and which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.
The present disclosure will be described herein below with reference to the accompanying drawings. In the following description, well known functions or constructions are not described in detail since they would obscure the description with unnecessary detail.
As used herein, the term “system” is used to refer to an arrangement of interconnected components which work collectively to perform a specific operation. The system is implemented using electronic, computational, or mechanical elements to achieve a defined objective. The system comprises multiple interconnected units, wherein each unit performs a different role while contributing to an overall process. The system incorporates hardware and software-based elements to execute operations in a structured manner. The system processes data, executes computations, and transmits information across various interconnected components. The system operates within a predefined set of parameters to facilitate interaction among associated components. The system functions autonomously or in coordination with external entities to maintain operational integrity. The system employs standardized methods to exchange information and execute assigned operations.
As used herein, the term “control unit” is used to refer to an electronic unit which manages operations of an associated system by executing predefined instructions. The control unit processes incoming data and regulates interactions with external components to maintain operational coherence. The control unit facilitates bidirectional communication between interconnected components through an established interface. The control unit interprets received data and executes corresponding actions based on predefined instructions. The control unit governs data exchange and enables secure communication with external entities. The control unit receives, processes, and transmits information in accordance with established protocols. The control unit stores operational parameters that define execution of specific processes. The control unit facilitates integration of multiple subsystems by coordinating transmission and reception of data. The control unit maintains a data flow to prevent unauthorized modifications. The control unit executes verification mechanisms to validate authenticity of received information.
As used herein, the term “security verification unit” is used to refer to a unit that monitors operational integrity of software by detecting potential cyber-attacks. The security verification unit continuously evaluates data exchanged between interconnected components to identify anomalies. The security verification unit applies predefined verification techniques to determine authenticity of received information. The security verification unit executes security checks to detect unauthorized modifications within an associated software. The security verification unit processes cryptographic verification techniques to authenticate legitimacy of software operations. The security verification unit evaluates transmitted and received data to identify threats. The security verification unit conducts periodic security assessments to detect deviations from predefined security standards. The security verification unit assures compliance with security parameters by verifying consistency of operational data. The security verification unit executes authentication mechanisms to validate integrity of received information.
As used herein, the term “hash value computation unit” is used to refer to a unit whicht generates a unique hash value corresponding to a software based on content integrity. The hash value computation unit processes input data using a predefined hashing function to compute a hash value. The hash value computation unit applies cryptographic techniques to derive a unique identifier for a specific software. The hash value computation unit assures consistency of hash values by applying predefined computational procedures. The hash value computation unit executes transformation of data into a fixed-length representation based on hashing methodologies. The hash value computation unit generates a current hash value for integrity verification purposes. The hash value computation unit transmits computed hash values for validation against a reference standard. The hash value computation unit maintains data confidentiality by preventing unauthorized modifications of computed hash values. The hash value computation unit processes cryptographic transformations to assure uniqueness of generated hash values.
As used herein, the term “data reception unit” is used to refer to a unit that acquires reference data from a remotely located data repository. The data reception unit retrieves predefined information to facilitate validation of system operations. The data reception unit receives a predetermined hash value for integrity verification. The data reception unit communicates with a remotely located database to obtain reference parameters. The data reception unit processes incoming data to establish reference standards for validation. The data reception unit facilitates secure retrieval of verification data from an external repository. The data reception unit executes authentication procedures to assure validity of received reference information. The data reception unit synchronizes with a remote server to acquire integrity verification data.
As used herein, the term “comparison unit” is used to refer to a unit which evaluates integrity of software by comparing computed hash values with reference hash values. The comparison unit receives hash values from a hash value computation unit and a data reception unit. The comparison unit applies predefined verification techniques to determine whether discrepancies exist between received hash values. The comparison unit analyzes consistency of received data to detect unauthorized modifications. The comparison unit processes integrity checks to identify deviations from reference standards. The comparison unit evaluates received data to detect potential cybersecurity threats.
As used herein, the term “warning generation unit” is used to refer to a unit that processes validation results from a comparison unit and issues an alert upon detection of a cyber-attack. The warning generation unit categorizes detected cyber-attacks based on predefined severity levels. The warning generation unit issues an alert for identification of a compromised charging station. The warning generation unit transmits security notifications to a fleet of electric vehicles. The warning generation unit processes detected anomalies to enable cybersecurity awareness. The warning generation unit executes alert transmission mechanisms to assure dissemination of cybersecurity warnings. The warning generation unit facilitates real-time notification of detected cybersecurity breaches. The warning generation unit applies predefined assessment criteria to classify severity of detected threats.
As used herein, the term “display interface” is used to refer to an interface that presents visual indicators on a digital map. The display interface marks an identified charging station involved in a cyber-attack. The display interface renders graphical representations of cybersecurity events on a display screen. The display interface updates a digital map to indicate cybersecurity status of multiple charging stations. The display interface applies a color-coded scheme to differentiate charging stations based on cybersecurity risk levels. The display interface presents real-time cybersecurity information for a fleet of electric vehicles. The display interface facilitates identification of cybersecurity threats by rendering graphical alerts. The display interface provides a representation of compromised charging stations. The display interface enables visualization of cybersecurity events through digital mapping techniques.
FIG. 1 illustrates a system 100 to enhance cybersecurity during charging of a battery of an electric vehicle at a charging station, in accordance with embodiments of the present disclosure. The system 100 comprises a control unit 102 which is positioned within the electric vehicle and exchanges data with the charging station through a communication interface during a charging operation. The control unit 102 establishes a secure communication session by authenticating the charging station before data exchange begins. The control unit 102 retrieves charging parameters, including power levels, voltage, and session duration, and transmits vehicle authentication data to the charging station. The control unit 102 applies encryption techniques to protect transmitted and received data from unauthorized modifications. The control unit 102 continuously monitors communication signals and logs transactional records to detect anomalies in the charging session. The control unit 102 synchronizes with external security systems to retrieve updated security policies and enforce compliance with predefined cybersecurity measures. The control unit 102 restricts data exchange if unauthorized communication attempts are detected. The control unit 102 transmits real-time alerts to a fleet management server if discrepancies in authentication credentials or session parameters are identified.
In an embodiment, the system 100 comprises a security verification unit 104 that monitors the integrity of software stored within the control unit 102 by detecting potential cyber-attacks occurring during the charging operation. The security verification unit 104 retrieves predefined security baselines and applies digital signature validation techniques to verify the authenticity of stored software. The security verification unit 104 detects unauthorized software modifications by comparing stored integrity parameters against validated reference values. The security verification unit 104 continuously scans software execution logs and detects anomalies that indicate cybersecurity risks. The security verification unit 104 transmits software verification results to an external cybersecurity monitoring system for further assessment. The security verification unit 104 prevents execution of unauthorized software by enforcing predefined access restrictions if discrepancies are detected. The security verification unit 104 applies cryptographic authentication techniques to validate system updates before installation.
In an embodiment, the system 100 comprises a hash value computation unit 106 that generates a current hash value corresponding to the software by applying a secure hashing function to process input software data and generate a unique identifier representing software integrity. The hash value computation unit 106 executes a cryptographic hashing process to transform software data into a fixed-length representation. The hash value computation unit 106 prevents unauthorized software modifications by detecting inconsistencies in computed hash values over time. The hash value computation unit 106 applies a non-reversible transformation process, preventing reconstruction of original software content from generated hash values. The hash value computation unit 106 synchronizes with the security verification unit 104 to facilitate real-time integrity monitoring. The hash value computation unit 106 transmits generated hash values to a comparison unit 110 over an encrypted communication channel, assuring secure validation of software integrity. The hash value computation unit 106 processes hash values at predefined intervals to continuously verify software authenticity.
In an embodiment, the system 100 comprises a data reception unit 108 that acquires a predetermined hash value from a remotely located data repository, wherein the predetermined hash value represents a reference for integrity verification. The data reception unit 108 establishes a secure connection with an external cybersecurity repository and retrieves the most recent validated hash values for stored software. The data reception unit 108 prevents unauthorized access to retrieved reference hash values by applying encryption techniques during transmission. The data reception unit 108 validates the authenticity of retrieved hash values before transmitting them to the comparison unit 110 for verification.
In an embodiment, the comparison unit 110 receives the current hash value from the hash value computation unit 106 and the predetermined hash value from the data reception unit 108, respectively, wherein the comparison unit 110 determines if the software is compromised through a hash value comparison. The comparison unit 110 executes automated validation of computed and reference hash values, identifying discrepancies indicative of unauthorized software modifications. The comparison unit 110 prevents execution of compromised software by transmitting security alerts to the security verification unit 104. The comparison unit 110 logs detected integrity violations for forensic analysis, enabling tracking of historical cybersecurity incidents. The comparison unit 110 synchronizes with the external cybersecurity monitoring system to facilitate automated threat detection and risk assessment. The comparison unit 110 prevents unauthorized modifications to stored hash comparison logs by applying cryptographic encryption techniques. The comparison unit 110 retrieves past integrity verification results and applies statistical analysis to identify trends in cyber-attack patterns.
In an embodiment, the system 100 comprises a warning generation unit 112 that processes the results from the comparison unit 110 and issues an alert upon detecting a cyber-attack, wherein the alert enables identification of the charging station involved in the cyber-attack, and the issued alert is transmitted to a fleet of electric vehicles. The warning generation unit 112 categorizes detected cybersecurity threats based on predefined risk classification criteria, enabling prioritization of response actions. The warning generation unit 112 transmits real-time security alerts to an external fleet management server, assuring cybersecurity awareness across the fleet of electric vehicles. The warning generation unit 112 prevents unauthorized modification of alert messages by applying cryptographic authentication techniques before transmission.
In an embodiment, the system 100 comprises a display interface 114 that renders a visual indicator on a digital map, wherein the digital map marks the identified charging station involved in the cyber-attack, and the digital map is presented on the display screens of the fleet of electric vehicles. The display interface 114 retrieves cybersecurity assessment results from the warning generation unit 112 and visually represents compromised, high-risk, and secure charging stations using predefined color codes. The display interface 114 marks compromised charging stations in red, charging stations under investigation in yellow, and secure charging stations in green, enabling electric vehicle users to make informed charging decisions. The display interface 114 synchronizes real-time risk assessment updates across the fleet of electric vehicles to assure uniform cybersecurity awareness. The display interface 114 prevents display of outdated security status by continuously refreshing the digital map based on the latest threat intelligence data. The display interface 114 integrates with external cybersecurity monitoring frameworks to validate the accuracy of displayed risk assessments before updating the digital map. The display interface 114 restricts user access to high-risk charging stations by displaying alert messages that notify of cybersecurity threats.
In an exemplary use case scenario, during a routine charging operation at a public charging station, an electric vehicle establishes a connection with the charging station through a communication interface managed by the control unit 102. The control unit 102 exchanges authentication credentials and charging parameters with the charging station while monitoring data exchange integrity. The security verification unit 104 continuously analyzes software integrity within the control unit 102, identifying any unauthorized modifications or anomalies in data transmission. The hash value computation unit 106 generates a current hash value corresponding to the software stored within the control unit 102 and forwards the generated current hash value for validation. The data reception unit 108 retrieves a predetermined hash value from a remotely located data repository, wherein the predetermined hash value represents a reference for verifying software integrity. The comparison unit 110 receives both the current hash value and the predetermined hash value and executes a hash value comparison to determine if software within the control unit 102 has been compromised. Upon detection of software discrepancies indicating a cyber-attack, the warning generation unit 112 processes validation results and issues the alert identifying the compromised charging station. The issued alert is transmitted to a fleet of electric vehicles to prevent further cybersecurity breaches. The display interface 114 updates a digital map with a visual indicator marking the identified charging station, wherein the digital map is presented on display screens of the fleet of electric vehicles, enabling users to avoid the compromised charging station and mitigating risks associated with cyber-attacks on electric vehicle charging infrastructure.
In an embodiment, the security verification unit 104 may employ a cryptographic verification technique to detect whether software stored within the control unit 102 is compromised. The cryptographic verification technique applies an asymmetric encryption method for authentication of the software. The asymmetric encryption method utilizes a pair of cryptographic keys, comprising a private key and a public key, to execute the authentication process. The security verification unit 104 retrieves a digital signature associated with the software and applies the public key to validate authenticity. The security verification unit 104 verifies whether the software has been altered by comparing the computed digital signature with an expected reference signature. The security verification unit 104 prevents unauthorized execution of software that fails authentication. The security verification unit 104 communicates with a remote security management system to retrieve updated public keys for verification purposes. The security verification unit 104 transmits alerts upon detection of an unauthorized modification. The security verification unit 104 applies encryption mechanisms to prevent interception of cryptographic authentication data. The security verification unit 104 verifies software integrity at predefined intervals to maintain cybersecurity compliance. The security verification unit 104 restricts execution of unsigned software to prevent unauthorized access. The security verification unit 104 applies a secure authentication method that prevents brute-force attacks by assuring cryptographic key confidentiality.
In an embodiment, the hash value computation unit 106 may apply a secure hashing function to generate a current hash value corresponding to software stored within the control unit 102. The secure hashing function is selected from a set consisting of SHA-256, SHA-3, and Blake2. The hash value computation unit 106 processes an input software file to generate a unique, fixed-length hash value that represents the integrity of the software. The hash value computation unit 106 assures that even a minor modification in the software results in a significantly different hash value. The hash value computation unit 106 processes input data in a one-way transformation to prevent reconstruction of the original content. The hash value computation unit 106 transmits the generated hash value to the comparison unit 110 for validation. The hash value computation unit 106 maintains computational efficiency by optimizing hash value generation during runtime execution. The hash value computation unit 106 integrates with security verification unit 104 to execute real-time hashing of software components. The hash value computation unit 106 applies a non-reversible cryptographic process to assure data confidentiality. The hash value computation unit 106 applies hashing methodologies that prevent unauthorized tampering by validating software integrity against a reference hash value. The hash value computation unit 106 generates hash values that are resistant to collision attacks by implementing cryptographic security standards.
In an embodiment, the comparison unit 110 may store a historical record of hash value comparisons to facilitate forensic analysis of cyber-attacks. The historical record is encrypted and stored within a secure data repository. The comparison unit 110 maintains an indexed database of previously computed hash values for reference during security analysis. The comparison unit 110 applies cryptographic security measures to prevent unauthorized modification of stored records. The comparison unit 110 retrieves historical hash values to analyze recurring cybersecurity threats. The comparison unit 110 transmits encrypted hash value records to an external security monitoring system for further analysis. The comparison unit 110 applies integrity validation techniques to prevent corruption of stored hash value records. The comparison unit 110 enables identification of attack patterns by referencing historical hash values against current computations. The comparison unit 110 restricts access to stored hash values to authorized security management systems. The comparison unit 110 applies real-time logging mechanisms to continuously update historical records of hash value comparisons.
In an embodiment, a certificate validation unit may verify the validity of a software certificate associated with the charging station, and a connection control unit enables a data connection to the charging station only if the software certificate is valid. The certificate validation unit retrieves a digital certificate from the charging station and verifies authenticity using a certificate authority. The certificate validation unit assures that the software certificate has not expired or been revoked. The certificate validation unit applies a cryptographic validation process to authenticate the certificate. The certificate validation unit transmits validation results to the connection control unit. The connection control unit establishes a secure connection with the charging station only upon successful certificate authentication. The connection control unit prevents communication with an unauthorized charging station lacking a valid certificate. The connection control unit applies predefined security policies to determine whether to permit data exchange. The connection control unit communicates with a remote certificate management system to retrieve updated security credentials.
In an embodiment, a certificate management unit may revoke a currently valid software certificate of the charging station upon detection of the cyber-attack. The certificate management unit retrieves a compromised certificate and transmits a revocation request to a certificate authority. The certificate management unit updates a certificate revocation list to prevent further communication with the compromised charging station. The certificate management unit applies a cryptographic signing process to authenticate revocation requests. The certificate management unit transmits revocation notifications to security management servers for immediate enforcement. The certificate management unit prevents unauthorized use of a compromised certificate by marking compromised certificate as invalid. The certificate management unit coordinates with external security frameworks to assure consistent enforcement of revocation policies. The certificate management unit updates security credentials of electric vehicles to reflect certificate revocation status. The certificate management unit integrates with a connection control unit to automatically block communication with charging stations operating with revoked certificates.
In an embodiment, the warning generation unit 112 may categorize the detected cyber-attack based on severity levels before issuance of the alert, wherein the severity levels are determined based on a predefined risk assessment matrix. The warning generation unit 112 analyzes characteristics of a detected cyber-attack by evaluating parameters comprising unauthorized access attempts, integrity violations, and anomalies in data exchange. The warning generation unit 112 assigns the severity level to the detected cyber-attack based on predefined assessment criteria, wherein severity levels are classified as low, moderate, high, or critical. The warning generation unit 112 references historical cyber-attack records stored within the comparison unit 110 to determine the frequency and impact of the detected cyber-attack. The warning generation unit 112 applies rule-based classification techniques to differentiate between minor security breaches and major cybersecurity threats. The warning generation unit 112 transmits severity classification results to the cybersecurity monitoring system for real-time assessment. The warning generation unit 112 issues alerts with severity indicators to inform electric vehicle users and fleet management entities about the cybersecurity risks associated with the charging station. The warning generation unit 112 facilitates automated cybersecurity response actions based on the assigned severity level, wherein high-severity cyber-attacks may trigger immediate disconnection from the compromised charging station.
In an embodiment, the display interface 114 may update the digital map to indicate a real-time cybersecurity status of multiple charging stations, wherein a color-coded scheme is applied to differentiate the charging stations based on cybersecurity risk levels. The display interface 114 retrieves real-time cybersecurity assessment data from the warning generation unit 112 to reflect the latest security status of charging stations. The display interface 114 applies different color codes to categorize charging stations based on identified security threats, wherein green represents a secure charging station, yellow indicates a station under investigation, and red marks a compromised station. The display interface 114 dynamically updates the digital map to provide electric vehicle users with real-time cybersecurity information. The display interface 114 integrates with a fleet management system to synchronize security status updates across multiple electric vehicles. The display interface 114 applies geographic mapping techniques to enable visualization of compromised charging stations within a specified region. The display interface 114 retrieves historical cybersecurity records to provide context on previously compromised charging stations. The display interface 114 facilitates user navigation by recommending alternative secure charging stations based on real-time security updates.
In an embodiment, the warning generation unit 112 may transmit the alert to a fleet management server in addition to the fleet of electric vehicles, wherein the fleet management server logs cyber-attack incidents and generates analytical reports for cybersecurity monitoring. The warning generation unit 112 processes detected cybersecurity incidents and generates the alert containing details of the compromised charging station, severity classification, and recommended security actions. The warning generation unit 112 transmits the generated alert to a centralized fleet management server for real-time monitoring of cybersecurity threats affecting electric vehicle infrastructure. The fleet management server maintains a database of historical cyber-attack incidents, enabling trend analysis and risk prediction. The fleet management server applies automated data processing techniques to generate analytical reports highlighting cybersecurity vulnerabilities and high-risk charging stations. The fleet management server facilitates communication between electric vehicle operators and cybersecurity authorities by providing detailed records of detected cyber-attacks. The fleet management server generates periodic cybersecurity assessment reports to inform fleet operators about risks. The fleet management server applies machine learning-based threat detection methodologies to predict recurring cybersecurity threats based on stored cyber-attack data.
In an embodiment, the security verification unit 104 may check periodic integrity of software beyond the charging operation, wherein the periodic integrity checks are scheduled based on a predefined time interval or triggered by anomaly detection mechanisms. The security verification unit 104 retrieves a predefined schedule specifying time intervals for executing periodic integrity verification of software stored within the control unit 102. The security verification unit 104 applies integrity verification techniques at predefined time intervals to detect unauthorized modifications that may occur outside of charging operations. The security verification unit 104 executes on-demand integrity checks upon detection of anomalous behavior within an electric vehicle control system. The security verification unit 104 synchronizes with external cybersecurity monitoring systems to assure periodic verification procedures align with updated security policies. The security verification unit 104 maintains detailed logs of periodic integrity verification results for forensic analysis of detected cybersecurity breaches. The security verification unit 104 applies cryptographic validation techniques to authenticate software integrity during scheduled verification cycles. The security verification unit 104 transmits periodic integrity verification reports to an external cybersecurity framework for compliance assessment. The security verification unit 104 prevents execution of unauthorized software detected during periodic verification by enforcing security policies restricting unverified modifications. The security verification unit 104 applies predefined security parameters to determine acceptable thresholds for software modifications.
FIG. 2 illustrates a method 200 to enhance cybersecurity during charging of the battery of the electric vehicle at the charging station, in accordance with embodiments of the present disclosure. At step 202, the control unit 102 positioned within the electric vehicle receives data from the charging station through a communication interface during a charging operation. The control unit 102 establishes a secure communication channel with the charging station and exchanges authentication credentials, charging session parameters, and operational data. At step 204, the security verification unit 104 monitors the integrity of software stored within the control unit 102 by detecting potential cyber-attacks occurring during the charging operation. The security verification unit 104 retrieves predefined security baselines and applies digital signature verification techniques to validate the authenticity of software files. At step 206, the hash value computation unit 106 generates a current hash value corresponding to the software by applying a secure hashing function to process input software data and generate a unique identifier representing software integrity. At step 208, the hash value computation unit 106 forwards the generated current hash value for validation, transmitting current hash value over a secure communication channel to the comparison unit 110 to prevent unauthorized modifications. At step 210, the data reception unit 108 acquires a predetermined hash value from a remotely located data repository, wherein the predetermined hash value represents a reference for integrity verification. The data reception unit 108 establishes a secure connection with an external security repository and retrieves the reference hash value for validation. At step 212, the comparison unit 110 compares the current hash value with the predetermined hash value to determine whether the software is compromised, executing verification procedures to detect inconsistencies in integrity. At step 214, the warning generation unit 112 processes the results from the comparison unit 110 and analyzes detected discrepancies, categorizing the detected cyber-attack based on severity levels determined through a predefined risk assessment matrix. At step 216, the warning generation unit 112 issues an alert upon detecting a cyber-attack, identifying the charging station involved in the cyber-attack. At step 218, the warning generation unit 112 transmits the alert to a fleet of electric vehicles to assure cybersecurity awareness among connected vehicles. At step 220, the display interface 114 renders a visual indicator on a digital map, marking the identified charging station involved in the cyber-attack and presenting the updated cybersecurity status on display screens of the fleet of electric vehicles.
In an embodiment, the security verification unit 104 may perform a multi-factor validation process to verify integrity of both control unit 102 firmware and external communication logs associated with the control unit 102. The security verification unit 104 retrieves predefined security baselines for firmware validation and executes digital signature verification techniques to confirm authenticity of firmware components. The security verification unit 104 compares stored firmware hashes against reference hash values retrieved from a secure repository to detect unauthorized modifications. The security verification unit 104 logs detected discrepancies and transmits verification results to an external cybersecurity monitoring system. The security verification unit 104 applies sequential validation methods to confirm consistency of external communication logs. The security verification unit 104 retrieves communication logs from the control unit 102 and analyzes recorded data for unauthorized access attempts. The security verification unit 104 validates transmission history by comparing logged communication events against expected operational patterns. The security verification unit 104 applies timestamp validation to assure logs remain unaltered since their creation. The security verification unit 104 restricts execution of unverified firmware to prevent unauthorized modifications. The security verification unit 104 synchronizes validation results with remote cybersecurity frameworks to facilitate real-time assessment of control unit 102 integrity. The security verification unit 104 executes continuous validation cycles at predefined intervals to maintain cybersecurity compliance.
In an embodiment, the warning generation unit 112 may generate the alert comprising a geofencing mechanism restricting access to the charging station by disabling charging authorization for battery-electric vehicles within a predefined proximity of the charging station. The warning generation unit 112 processes real-time location data of the electric vehicle and compares proximity coordinates against a restricted geofenced area. The warning generation unit 112 determines whether the electric vehicle is approaching the charging station associated with detected cybersecurity threats. The warning generation unit 112 transmits a charging authorization restriction command to a charging station management system upon detecting the electric vehicle within the restricted geofenced area. The warning generation unit 112 prevents activation of charging sessions at a compromised charging station to mitigate cybersecurity risks. The warning generation unit 112 synchronizes geofencing parameters with a fleet management system to assure consistent enforcement of access restrictions across multiple electric vehicles. The warning generation unit 112 retrieves updated geofencing parameters from a cybersecurity monitoring network to reflect real-time security assessments. The warning generation unit 112 transmits geofencing restriction notifications to electric vehicle users to inform about restricted charging stations.
In an embodiment, the security verification unit 104 may utilize an artificial intelligence-based anomaly detection mechanism to predict potential cyber-attacks before software compromise occurs based on deviations in charging station communication patterns. The security verification unit 104 retrieves historical communication data of the charging station and applies predictive modeling techniques to identify behavioral deviations. The security verification unit 104 detects anomalies in data exchange by analyzing inconsistencies in authentication sequences, transaction timestamps, and encryption parameters. The security verification unit 104 applies machine learning-based classification techniques to differentiate between normal communication patterns and cyber threats. The security verification unit 104 continuously updates anomaly detection models by incorporating newly identified cybersecurity incidents into training datasets. The security verification unit 104 processes real-time network traffic logs and identifies unauthorized communication attempts indicative of cyber-attacks. The security verification unit 104 synchronizes detected anomalies with external threat intelligence databases to compare against known cybersecurity threats. The security verification unit 104 assigns risk scores to detected anomalies based on predefined classification parameters. The security verification unit 104 transmits predictive security alerts to cybersecurity monitoring entities before a cyber-attack leads to software compromise.
In an embodiment, the warning generation unit 112 may transmit the alert through a decentralized blockchain-based cybersecurity framework to prevent tampering and unauthorized modification of alert data. The warning generation unit 112 generates a cryptographically secured alert containing details of detected cybersecurity threats, comprising compromised charging stations and affected electric vehicles. The warning generation unit 112 transmits the alert to a blockchain network for decentralized storage and validation. The warning generation unit 112 applies cryptographic hashing techniques to secure alert contents against unauthorized modifications. The warning generation unit 112 prevents centralized manipulation of cybersecurity alert records by distributing alert data across multiple blockchain nodes. The warning generation unit 112 synchronizes alert records with a distributed ledger to enable real-time verification of cybersecurity threats. The warning generation unit 112 assures transparency of cybersecurity notifications by enabling blockchain-based traceability of issued alerts. The warning generation unit 112 retrieves previously stored alert records from a blockchain ledger to validate historical cybersecurity events. The warning generation unit 112 transmits blockchain-stored alerts to cybersecurity monitoring systems for further analysis and response coordination. The warning generation unit 112 applies smart contract validation mechanisms to enforce predefined security policies before processing alert data. The warning generation unit 112 prevents unauthorized suppression or alteration of cybersecurity alerts by enforcing decentralized verification through blockchain consensus mechanisms.
In an embodiment, the control unit 102 positioned within the electric vehicle exchanges data with the charging station through a communication interface during the charging operation. The control unit 102 facilitates secure authentication and transmission of charging parameters, preventing unauthorized access to internal systems of the electric vehicle. The control unit 102 applies encryption techniques to safeguard transmitted data against cyber threats. The control unit 102 continuously monitors communication traffic for anomalies indicative of cybersecurity risks. The control unit 102 establishes a data exchange framework, reducing latency and improving reliability of charging session management. The control unit 102 synchronizes with external cybersecurity systems to receive updated threat intelligence, preventing unauthorized charging sessions initiated by compromised charging stations. The control unit 102 prevents unauthorized firmware updates from unverified sources, maintaining operational integrity of vehicle control mechanisms.
In an embodiment, the security verification unit 104 monitors integrity of software stored within the control unit 102 by detecting potential cyber-attacks occurring during the charging operation. The security verification unit 104 applies real-time software integrity verification techniques to detect unauthorized modifications. The security verification unit 104 continuously scans software execution patterns, identifying irregularities that indicate cybersecurity breaches. The security verification unit 104 prevents execution of compromised software by restricting access to system resources. The security verification unit 104 validates integrity of installed software against reference security baselines retrieved from a remote cybersecurity framework. The security verification unit 104 prevents unauthorized code injections by applying signature verification techniques before executing system updates. The security verification unit 104 synchronizes with the fleet management server to report detected security anomalies, enabling real-time risk mitigation.
In an embodiment, the hash value computation unit 106 generates a current hash value corresponding to software stored within the control unit 102. The hash value computation unit 106 applies a secure hashing function to transform input software data into a unique fixed-length hash value. The hash value computation unit 106 prevents unauthorized software modifications by detecting inconsistencies in hash values computed before and after system updates. The hash value computation unit 106 assures non-reversibility of hash values, preventing reconstruction of original software content from stored hash outputs. The hash value computation unit 106 synchronizes hash computation with predefined security verification schedules to assure continuous monitoring of software integrity. The hash value computation unit 106 prevents hash collision attacks by utilizing improved cryptographic hashing functions, maintaining unique identifiers for software files.
In an embodiment, the data reception unit 108 acquires a predetermined hash value from a remotely located data repository, wherein the predetermined hash value represents a reference for integrity verification. The data reception unit 108 establishes a secure communication channel with an external cybersecurity repository to retrieve validated hash values. The data reception unit 108 prevents unauthorized access to reference hash values by applying encryption techniques during data transmission. The data reception unit 108 synchronizes acquired hash values with predefined integrity verification cycles, assuring consistency in software validation. The data reception unit 108 prevents outdated integrity verification results by retrieving the most recent hash values associated with control unit 102 firmware. The data reception unit 108 validates authenticity of retrieved reference hash values before transmitting them for comparison, mitigating risks of compromised integrity validation data.
In an embodiment, the comparison unit 110 receives the current hash value from the hash value computation unit 106 and the predetermined hash value from the data reception unit 108, respectively, and determines if the software is compromised through a hash value comparison. The comparison unit 110 executes automated validation of computed and reference hash values, identifying discrepancies indicative of unauthorized software modifications. The comparison unit 110 prevents execution of software that fails integrity verification by transmitting security alerts to the control unit 102. The comparison unit 110 logs detected integrity violations for forensic analysis, enabling tracking of historical cybersecurity incidents. The comparison unit 110 synchronizes with the external cybersecurity monitoring system to facilitate automated threat detection and risk assessment. The comparison unit 110 prevents unauthorized modifications to stored hash comparison logs by applying cryptographic encryption techniques.
In an embodiment, the warning generation unit 112 processes results from the comparison unit 110 and issues the alert upon detecting a cyber-attack, wherein the alert enables identification of the charging station involved in the cyber-attack. The warning generation unit 112 categorizes detected cybersecurity threats based on predefined risk classification criteria, enabling prioritization of response actions. The warning generation unit 112 transmits real-time security alerts to the fleet of electric vehicles, preventing further exposure to compromised charging stations. The warning generation unit 112 prevents unauthorized modification of alert messages by applying digital signature verification before transmission. The warning generation unit 112 synchronizes with an external cybersecurity framework to improve real-time threat intelligence reporting. The warning generation unit 112 assures secure storage of cybersecurity incident reports by encrypting alert records stored within a fleet management system.
In an embodiment, the display interface 114 renders a visual indicator on a digital map, marking the identified charging station involved in a cyber-attack. The display interface 114 categorizes charging stations based on cybersecurity risk levels, enabling electric vehicle users to make informed decisions. The display interface 114 updates digital map indicators in real-time, preventing outdated security information from misleading electric vehicle operators. The display interface 114 integrates with fleet management dashboards to facilitate centralized cybersecurity monitoring across multiple electric vehicles. The display interface 114 synchronizes with external cybersecurity monitoring networks to assure accuracy of displayed risk assessment data. The display interface 114 prevents unauthorized tampering of cybersecurity indicators by applying cryptographic security mechanisms before rendering visual alerts.
In an embodiment, the security verification unit 104 employs a cryptographic verification technique to detect whether software stored within the control unit 102 is compromised, wherein the cryptographic verification technique comprises an asymmetric encryption method for authentication of the software. The security verification unit 104 retrieves a public key from a trusted certificate authority and applies asymmetric encryption techniques to verify the authenticity of software signatures. The security verification unit 104 assures that only software signed with a corresponding private key is permitted to execute within the control unit 102. The security verification unit 104 prevents unauthorized modifications by rejecting software files that fail cryptographic signature verification. The security verification unit 104 applies digital certificate validation to assure that only verified software updates are installed within the control unit 102. The security verification unit 104 prevents brute-force attacks by applying cryptographic authentication techniques that require computationally intensive validation procedures. The security verification unit 104 synchronizes with an external certificate authority to retrieve updated cryptographic verification credentials, preventing unauthorized software executions.
In an embodiment, the hash value computation unit 106 applies a secure hashing function to generate a current hash value corresponding to software stored within the control unit 102, wherein the secure hashing function is selected from a set consisting of SHA-256, SHA-3, and Blake2. The hash value computation unit 106 processes software input data using cryptographic hashing functions to generate a unique, fixed-length hash value. The hash value computation unit 106 prevents unauthorized software modifications by assuring that even minor alterations result in significantly different hash values. The hash value computation unit 106 applies non-reversible cryptographic transformations to assure that the original software content cannot be reconstructed from computed hash values. The hash value computation unit 106 synchronizes hash value computations with predefined verification intervals to maintain real-time software integrity monitoring. The hash value computation unit 106 prevents hash collision attacks by utilizing cryptographic functions resistant to brute-force tampering. The hash value computation unit 106 transmits computed hash values to the comparison unit 110 over a secure channel, assuring protected validation of software integrity.
In an embodiment, the comparison unit 110 stores a historical record of hash value comparisons to facilitate forensic analysis of cyber-attacks, wherein the historical record is encrypted and stored within a secure data repository. The comparison unit 110 maintains a log of previously computed hash values to enable tracking of unauthorized software modifications over time. The comparison unit 110 prevents data manipulation by applying encryption techniques to secure stored hash comparison records. The comparison unit 110 assures consistency of stored hash values by implementing validation mechanisms that detect unauthorized modifications to historical records. The comparison unit 110 retrieves past hash value comparisons to analyze recurring cybersecurity threats affecting control unit 102 software. The comparison unit 110 transmits stored hash value records to the external cybersecurity monitoring system to facilitate risk assessment and cybersecurity auditing. The comparison unit 110 enables forensic analysis of cybersecurity incidents by maintaining an immutable log of integrity verification results.
In an embodiment, the certificate validation unit verifies the validity of a software certificate associated with the charging station, and a connection control unit enables a data connection to the charging station only if the software certificate is valid. The certificate validation unit retrieves a digital certificate from the charging station and applies cryptographic validation techniques to verify authenticity. The certificate validation unit prevents unauthorized connections by rejecting certificates that fail integrity validation. The certificate validation unit synchronizes with an external certificate authority to retrieve updated certificate revocation lists, assuring that compromised certificates are not accepted. The connection control unit establishes a secure communication channel with the charging station only upon successful validation of the software certificate. The connection control unit prevents unauthorized access to vehicle systems by blocking data exchange with unverified charging stations. The connection control unit transmits security verification results to an external fleet management system to facilitate real-time cybersecurity monitoring.
In an embodiment, the certificate management unit revokes a currently valid software certificate of the charging station upon detection of a cyber-attack. The certificate management unit transmits a revocation request to a certificate authority, assuring that compromised certificates cannot be used for authentication. The certificate management unit updates a certificate revocation list and distributes the certificate revocation list to security monitoring systems, preventing unauthorized charging station access. The certificate management unit prevents reissuance of compromised certificates by coordinating with a trusted certificate authority. The certificate management unit transmits certificate revocation notifications to the fleet of electric vehicles to prevent unauthorized connections to the compromised charging station. The certificate management unit synchronizes with cybersecurity monitoring frameworks to maintain real-time enforcement of certificate revocation policies. The certificate management unit assures that revoked certificates are permanently blocked from authentication attempts by maintaining an immutable record of revocation actions.
In an embodiment, the warning generation unit 112 categorizes a detected cyber-attack based on severity levels before issuance of the alert, wherein the severity levels are determined based on a predefined risk assessment matrix. The warning generation unit 112 retrieves predefined cybersecurity assessment parameters to classify detected cyber threats based on impact, frequency, and risk to electric vehicle systems. The warning generation unit 112 assigns severity levels for example low, moderate, high, or critical based on deviations in expected software behavior and unauthorized modifications detected during verification. The warning generation unit 112 applies pattern recognition techniques to compare detected cybersecurity threats against historical attack records, assuring accurate classification of cyber-attacks. The warning generation unit 112 transmits categorized threat alerts to the external cybersecurity monitoring system to facilitate automated response coordination. The warning generation unit 112 prioritizes high-risk threats for immediate mitigation actions, comprising disconnecting a compromised charging station from network communications. The warning generation unit 112 assures that severity classification criteria are periodically updated by integrating real-time security intelligence data, preventing outdated assessment techniques from reducing detection accuracy.
In an embodiment, the display interface 114 updates a digital map to indicate a real-time cybersecurity status of multiple charging stations, wherein a color-coded scheme is applied to differentiate the charging stations based on cybersecurity risk levels. The display interface 114 retrieves cybersecurity assessment results from the warning generation unit 112 and visually represents compromised, high-risk, and secure charging stations using predefined color codes. The display interface 114 marks compromised charging stations in red, charging stations under investigation in yellow, and secure charging stations in green, enabling electric vehicle users to make informed charging decisions. The display interface 114 synchronizes real-time risk assessment updates across the fleet of electric vehicles to assure uniform cybersecurity awareness. The display interface 114 prevents display of outdated security status by continuously refreshing the digital map based on the latest threat intelligence data. The display interface 114 integrates with external cybersecurity monitoring frameworks to validate accuracy of displayed risk assessments before updating the digital map. The display interface 114 restricts user access to high-risk charging stations by displaying alert messages that notify of cybersecurity threats.
In an embodiment, the warning generation unit 112 transmits the alert to a fleet management server in addition to the fleet of electric vehicles, wherein the fleet management server logs cyber-attack incidents and generates analytical reports for cybersecurity monitoring. The warning generation unit 112 processes detected cyber-attacks and transmits alert data, comprising time of detection, nature of the attack, and the affected charging station, to a fleet management server. The warning generation unit 112 synchronizes transmitted alerts with fleet cybersecurity logs, assuring historical tracking of detected cybersecurity threats. The fleet management server stores transmitted alert data and executed analytical processing techniques to identify attack trends and high-risk locations. The fleet management server applies machine learning-based anomaly detection mechanisms to predict recurring cybersecurity risks based on logged incidents. The fleet management server retrieves cybersecurity analytics reports and transmits risk assessment summaries to electric vehicle operators for informed decision-making. The fleet management server prevents unauthorized modifications to logged cyber-attack records by applying cryptographic encryption techniques to secure stored alert data. The fleet management server enables centralized cybersecurity monitoring by integrating alert logs from multiple electric vehicles operating across different geographical locations.
In an embodiment, the security verification unit 104 checks periodic integrity of software beyond the charging operation, wherein the periodic integrity checks are scheduled based on a predefined time interval or triggered by anomaly detection mechanisms. The security verification unit 104 retrieves predefined verification schedules and executes integrity validation processes at regular intervals to detect unauthorized modifications to control unit 102 software. The security verification unit 104 prevents execution of tampered software by restricting access to system-critical resources if periodic integrity checks detect discrepancies. The security verification unit 104 synchronizes periodic integrity verification cycles with external cybersecurity monitoring systems to assure real-time assessment of software security. The security verification unit 104 retrieves anomaly detection reports and executes unscheduled integrity verification upon detecting unexpected software behavior. The security verification unit 104 prevents cybersecurity breaches by applying automated validation techniques before software modifications are executed. The security verification unit 104 transmits periodic integrity verification results to a fleet management server to assure cybersecurity compliance across the fleet of electric vehicles. The security verification unit 104 maintains detailed audit logs of periodic integrity checks to facilitate forensic analysis of detected cybersecurity incidents.
In an embodiment, the security verification unit 104 performs a multi-factor validation process comprising integrity verification of both control unit digital map interface diagram firmware and external communication logs associated with the control unit 102. The security verification unit 104 retrieves firmware integrity parameters and applies digital signature verification techniques to authenticate firmware authenticity before execution. The security verification unit 104 computes a hash value of stored firmware and compares against a reference hash value retrieved from a secure repository to detect unauthorized modifications. The security verification unit 104 verifies communication logs by analyzing historical data exchange records between the control unit 102 and external entities, identifying inconsistencies that indicate cybersecurity threats. The security verification unit 104 applies timestamp verification to validate communication log integrity, assuring that unauthorized log modifications are detected. The security verification unit 104 synchronizes multi-factor validation results with an external security monitoring framework, enabling centralized cybersecurity management. The security verification unit 104 prevents execution of unverified firmware by enforcing predefined security policies.
In an embodiment, the warning generation unit 112 generates the alert comprising a geofencing mechanism restricting access to the charging station by disabling charging authorization for battery-electric vehicles within a predefined proximity of the charging station. The warning generation unit 112 retrieves geolocation data of electric vehicles and applies geofencing parameters to define restricted zones around compromised charging stations. The warning generation unit 112 prevents electric vehicles from initiating charging sessions within restricted geofenced areas by transmitting authorization revocation commands to the charging station management system. The warning generation unit 112 synchronizes geofencing parameters with an external fleet management system to assure uniform enforcement of access restrictions across multiple vehicles. The warning generation unit 112 applies dynamic geofencing techniques, adjusting restricted zones based on real-time cybersecurity assessments. The warning generation unit 112 transmits security notifications to electric vehicle operators to inform them of access restrictions before arrival at a compromised charging station.
In an embodiment, the security verification unit 104 utilizes an artificial intelligence-based anomaly detection mechanism to predict potential cyber-attacks before software compromise occurs based on deviations in charging station communication patterns. The security verification unit 104 retrieves historical data exchange records from the control unit 102 and applies machine learning techniques to detect anomalies indicative of unauthorized access attempts. The security verification unit 104 processes authentication requests, data transmission timestamps, and encryption parameters to identify deviations from expected communication patterns. The security verification unit 104 assigns risk scores to detected anomalies, prioritizing high-risk deviations for immediate cybersecurity intervention. The security verification unit 104 synchronizes detected anomalies with an external cybersecurity intelligence database to validate threat signatures. The security verification unit 104 transmits predictive threat alerts to a cybersecurity monitoring system, enabling proactive mitigation measures before a cyber-attack occurs. The security verification unit 104 continuously updates anomaly detection models by incorporating real-time security intelligence, preventing outdated risk assessments.
In an embodiment, the warning generation unit 112 transmits the alert through a decentralized blockchain-based cybersecurity framework to prevent tampering and unauthorized modification of the alert data. The warning generation unit 112 generates cryptographically signed alert records and transmits them to a blockchain network for secure storage and validation. The warning generation unit 112 prevents unauthorized alteration of transmitted alerts by distributing alert data across multiple blockchain nodes. The warning generation unit 112 applies cryptographic hashing techniques to verify authenticity of stored alert data, assuring that cybersecurity notifications remain immutable. The warning generation unit 112 retrieves stored alert records from a distributed ledger and transmits them to the external cybersecurity monitoring system for real-time threat assessment. The warning generation unit 112 integrates with a blockchain-based consensus mechanism to assure that alert modifications require cryptographic validation by authorized security authorities. The warning generation unit 112 prevents centralized suppression of cybersecurity alerts by decentralized alert transmission mechanisms.
FIG. 3 illustrates a hash computation and comparison process diagram, in accordance with embodiments of the present disclosure. The hash computation and comparison process begin with the hash value computation unit 106 generating a current hash value corresponding to software integrity. The hash value computation unit 106 transmits said computed hash value to the comparison unit 110 for validation. Simultaneously, the data reception unit 108 requests a predetermined hash value from a remote data repository. The remote data repository retrieves and transmits the reference hash value to the data reception unit 108, which then forwards to the comparison unit 110 for integrity verification. The comparison unit 110 compares the current hash value with the predetermined hash value to determine software integrity status. If the values match, the software remains uncompromised, and validation is successful. If discrepancies exist, the comparison unit 110 identifies the software as compromised and flags a cybersecurity threat. The comparison unit 110 stores the comparison record for future forensic analysis, assuring that recurring cyber threats can be identified and mitigated effectively.
FIG. 4 illustrates a digital map interface diagram, in accordance with embodiments of the present disclosure. The digital map interface diagram display interface 114 updates and presents cybersecurity status of charging stations. The warning generation unit 112 processes cybersecurity data and identifies compromised charging stations. Said data is transmitted to display interface 114, which updates a digital map by marking affected charging stations. A color-coded risk level system is applied, where green represents secure stations, yellow indicates stations under review, and red marks compromised stations. The digital map is displayed to a fleet of electric vehicles, enabling users to make informed charging decisions. Simultaneously, display interface 114 synchronizes with a fleet management server, which logs cybersecurity alerts and supports real-time cybersecurity monitoring. The fleet management server assures all connected electric vehicles receive up-to-date cybersecurity information, preventing further interaction with compromised charging stations. The system continuously updates the digital map based on real-time cybersecurity assessments, assuring safe and secure charging infrastructure for electric vehicles.
In the description of the present invention, it is also to be noted that, unless otherwise explicitly specified or limited, the terms “disposed,” “mounted,” and “connected” are to be construed broadly, and may for example be fixedly connected, detachably connected, or integrally connected, either mechanically or electrically. They may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Modifications to embodiments and combination of different embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as “comprising”, “comprising”, “incorporating”, “have”, “is” used to describe and claim the present disclosure are intended to be construed in a non- exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural where appropriate.
Although embodiments have been described with reference to a number of illustrative embodiments thereof, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the spirit and scope of the principles of this disclosure. More particularly, various variations and modifications are possible in the component parts and/or arrangements of the subject combination arrangement within the scope of the present disclosure, the drawings and the appended claims. In addition to variations and modifications in the component parts and/or arrangements, alternative uses will also be apparent to those skilled in the art.
,CLAIMS:WE CLAIM:
1. A system 100 to enhance cybersecurity during charging of a battery of an electric vehicle at a charging station, the system 100 comprising:
a control unit 102 positioned within the electric vehicle, wherein the control unit 102 exchanges data with the charging station through a communication interface during a charging operation;
a security verification unit 104 monitors integrity of a software stored within the control unit 102 by detecting the potential cyber-attacks occurring during the charging operation;
a hash value computation unit 106 generating a current hash value corresponding to the software, wherein the hash value computation unit 106 forwards the generated current hash value for validation;
a data reception unit 108 acquires a predetermined hash value from a remotely located data repository, wherein the predetermined hash value representing a reference for integrity verification;
a comparison unit 110 receives the current hash value from the hash value computation unit 106 and the predetermined hash value from the data reception unit 108, respectively, wherein the comparison unit 110 determines, if the software is compromised through a hash value comparison;
a warning generation unit 112 processes the results from the comparison unit 110 and issues an alert upon detecting a cyber-attack, wherein the alert enables identification of the charging station involved in the cyber-attack, and the issued alert is transmitted to a fleet of the electric vehicles; and
a display interface 114 renders a visual indicator on a digital map, the digital map marks the identified charging station, wherein the digital map is presented on the display screens of the fleet of the electric vehicles.
2. The system 100 of claim 1, wherein the security verification unit 104 employs a cryptographic verification technique to detect whether the software is compromised, wherein the cryptographic verification technique comprises an asymmetric encryption for authentication of the software.
3. The system 100 of claim 1, wherein the hash value computation unit 106 applies a secure hashing function to generate the current hash value, wherein the secure hashing function is selected from a set consisting of SHA-256, SHA-3, and Blake2.
4. The system 100 of claim 1, wherein the comparison unit 110 stores a historical record of hash value comparisons to facilitate forensic analysis of the cyber-attacks, wherein the historical record is encrypted and stored within a secure data repository.
5. The system 100 of claim 1, further comprising:
a certificate validation unit to verify validity of a software certificate associated with the charging station; and
a connection control unit to enable a data connection to the charging station only if the software certificate is valid.
6. The system 100 of claim 5, further comprising a certificate management unit revoking a currently valid software certificate of the charging station upon detection of the cyber-attack.
7. The system 100 of claim 1, wherein the warning generation unit 112 categorizes the detected cyber-attack based on the severity levels before issuance of the alert, wherein the severity levels are determined based on a predefined risk assessment matrix.
8. The system 100 of claim 1, wherein the display interface 114 updates the digital map to indicate a real-time cybersecurity status of the multiple charging stations, wherein a color-coded scheme is applied to differentiate the charging stations based on the cybersecurity risk levels.
9. The system 100 of claim 1, wherein the warning generation unit 112 transmits the alert to a fleet management server in addition to the fleet of the electric vehicles, wherein the fleet management server logs the cyber-attack incidents and generates the analytical reports for cybersecurity monitoring.
10. The system 100 of claim 1, wherein the security verification unit 104 checks periodic integrity of the software beyond the charging operation, wherein the periodic integrity checks are scheduled based on a predefined time interval or triggered by the anomaly detection mechanisms.
11. A method 200 to enhance cybersecurity during charging of a battery of an electric vehicle at a charging station, the method 200 comprising:
receiving, by a control unit 102 positioned within the electric vehicle, data from the charging station through a communication interface during a charging operation;
monitoring, by a security verification unit 104, integrity of a software stored within the control unit 102 by detecting the potential cyber-attacks occurring during the charging operation;
generating, by a hash value computation unit 106, a current hash value corresponding to the software;
forwarding, by the hash value computation unit 106, the current hash value for validation;
acquiring, by a data reception unit 108, a predetermined hash value from a remotely located data repository, the predetermined hash value representing a reference for integrity verification;
comparing, by a comparison unit 110, the current hash value with the predetermined hash value to determine whether the software is compromised;
processing, by a warning generation unit 112, the results from the comparison unit 110;
issuing, by the warning generation unit 112, an alert upon detecting a cyber-attack, the alert identifying the charging station involved in the cyber-attack;
transmitting, by the warning generation unit 112, the alert to a fleet of the electric vehicles; and
rendering, by a display interface 114, a visual indicator on a digital map, the digital map marking the charging station involved in the cyber-attack, the digital map being presented on the display screens of the fleet of the electric vehicles.
12. The method 200 of claim 11, wherein a multi-factor validation process is performed by the security verification unit 104, wherein the multi-factor validation process comprises integrity verification of both control unit 102 firmware and external communication logs associated with the control unit 102.
13. The method 200 of claim 11, wherein the alert generated by the warning generation unit 112 comprises a geofencing mechanism restricting access to the charging station by disabling charging authorization for battery-electric vehicles within a predefined proximity of the charging station.
14. The method 200 of claim 11, wherein an artificial intelligence-based anomaly detection mechanism is utilized by the security verification unit 104 to predict potential cyber-attacks before software compromise occurs based on deviations in charging station communication patterns.
15. The method 200 of claim 11, wherein the warning generation unit 112 transmits the alert through a decentralized blockchain-based cybersecurity framework to prevent tampering and unauthorized modification of the alert data.