Description:

EMAIL ADDRESS TRACING FOR PROVIDING CYBERSECURITY
Field of the Invention
[0001] The present study pertains to the field of cybersecurity, more specifically to systems and methods for email address tracing as a means to enhance cybersecurity measures.
Background
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] Traditional approaches to cybersecurity have focused largely on perimeter defense mechanisms, such as firewalls and antivirus software. However, with the increasing sophistication of cyberattacks, especially those leveraging email as a primary vector, said traditional methods have shown significant limitations.
[0004] One of the primary drawbacks of prior art in the domain of email security is the reactive nature of threat detection and response. Conventional systems often rely on the identification of known malware signatures or patterns, which are ineffective against zero-day attacks or advanced persistent threats that use obfuscated techniques. In such cases, the delay between the emergence of a new threat and its identification by traditional security measures can leave systems vulnerable for extended periods.
[0005] Furthermore, prior art in said field has typically focused on endpoint protection, neglecting the intricacies involved in email communication per se. Said oversight has resulted in a lack of in-depth analysis of email traffic, which is critical for identifying more sophisticated attack vectors, such as spear phishing, where attackers use personalized information to deceive recipients. Such methods often bypass traditional security measures, as they do not carry recognizable malware signatures.
[0006] Additionally, the prior art has often lacked an approach to the analysis of metadata associated with emails. Metadata, such as IP addresses and email headers, provides information that can be used to trace the origin of emails and identify patterns indicative of malicious activity. However, existing systems have not effectively capitalized on said data, leading to missed opportunities for early detection of potential threats.
[0007] The static nature of threat databases in conventional systems is another limitation. Said databases require regular updates to remain effective, which can be a logistical challenge. The time lag in updating said databases can create windows of vulnerability, during which new threats can go undetected.
[0008] Moreover, many existing email security systems have been designed with a one-size-fits-all approach, lacking the flexibility to adapt to the unique security needs of different organizations or individuals. Said inflexibility can result in either inadequate security for complex environments or an unnecessary burden on smaller systems with simpler requirements.
[0009] The alert systems in prior art have also been a point of contention. Often, said systems generate a high volume of alerts, many of which are false positives. Said false positives can lead to alert fatigue among users, reducing the likelihood of prompt and appropriate responses to actual threats.
[00010] The traditional methods have struggled to keep pace with the evolving nature of email-based threats. The limitations of said methods, including their reactive nature, focus on endpoint protection, inadequate analysis of email traffic and metadata, reliance on static threat databases, lack of adaptability, and inefficient alert systems, have necessitated the development of more advanced, proactive, and solutions for email address tracing to effectively counteract cybersecurity threats. Thus, there exists a need in the art for a system to trace an email address for determination of a cybersecurity threat.

Summary
[00011] The present study pertains to the field of cybersecurity, more specifically to systems and methods for email address tracing as a means to enhance cybersecurity measures.
[00012] The following presents a simplified summary of various aspects of this disclosure in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements nor delineate the scope of such aspects. Its purpose is to present some concepts of this disclosure in a simplified form as a prelude to the more detailed description that is presented later.
[00013] The following paragraphs provide additional support for the claims of the subject application.
[00014] The disclosed study encompasses a system for tracing email addresses to determine cybersecurity threats, embodying a multi-faceted approach towards enhancing email security. Said system comprises four modules, each designed to address specific aspects of email-based threat detection and response.
[00015] Firstly, an email tracing module is employed, tasked with tracing incoming and outgoing email addresses. Said module meticulously records the email addresses involved in all email communications, providing a foundational dataset for further analysis. In an enhancement to said module, each incoming and outgoing email's timestamp is recorded, allowing for a chronological analysis of email traffic patterns. Said temporal data identifyies trends and anomalies in email communications.
[00016] Secondly, a data analysis module analyzes the traced email addresses. Said module conducts an assessment, including evaluation of sender and recipient information, analysis of IP addresses, and scrutiny of associated metadata. The analysis includes checking sender email addresses against a database of known malicious entities, assessing the frequency of email exchanges with particular addresses to identify unusual patterns, and evaluating recipient information to gauge potential internal threats. Additionally, said module incorporates a geographical tracking feature, flagging emails from or to suspicious locations, and examines email headers for spoofing signs.
[00017] Thirdly, a cybersecurity threat determination module is integral to the system. Said module compares the analyzed data against preconfigured threat criteria. To enhance the effectiveness of said process, the module utilizes machine learning algorithms. Said algorithms are continuously refined based on historical data, allowing for increasingly accurate threat detection.
[00018] Finally, an alert generation and response module completes the system's framework. Upon determination of a cybersecurity threat, said module generates notifications and initiates appropriate actions. Said response mitigates the impact of identified threats promptly.
[00019] Collectively, said modules form a system for email address tracing, tailored to identify and respond to a myriad of cybersecurity threats. The system's strength lies in the integrated approach, combining real-time tracing, detailed analysis, intelligent threat determination, and proactive response mechanisms. Said system addresses the limitations of existing methods by providing an adaptable, thorough, and responsive solution to safeguard against email-based cybersecurity threats, marking a significant advancement in the field of digital communication security.
[00020] In the contemporary digital landscape, the security of email communication stands as a paramount concern, necessitating advanced protective measures against escalating cybersecurity threats. In response to said need, a method for email address tracing to determine cybersecurity threats has been developed. Said method is detailed in scope, encompassing multiple steps, each meticulously designed to enhance email security through the identification and mitigation of potential threats.
[00021] The initial step in said method involves tracing both incoming and outgoing email addresses. Said tracing encompasses all emails that are sent and received, providing a foundational dataset from which potential threats can be assessed. The significance of said step lies in the capacity to gather extensive information about email communication patterns for subsequent analysis.
[00022] Subsequently, the traced email addresses are subjected to a thorough analysis. Said analysis extends beyond mere address tracking, encompassing a deep dive into the content of the emails. A pivotal aspect of said analysis includes language and content review to detect indicators of social engineering or phishing attempts. Said step is critical in identifying sophisticated cyberattacks that may not be evident through address tracing alone.
[00023] Upon the completion of the analysis, the method involves a step of determining cybersecurity threats. Said determination is based on a comparison of the analyzed data with preconfigured threat indicators. Such comparison enables the identification of discrepancies, anomalies, or known threat patterns, thereby facilitating the accurate detection of potential cybersecurity risks.
[00024] Finally, upon the determination of a cybersecurity threat, the method entails generating notifications and initiating appropriate actions. Said step is vital in ensuring that potential threats are not only identified but also adequately addressed. Actions may range from alerting users to implementing security protocols to mitigate the risk.
[00025] Thus, said method represents an approach to email security, combining the tracing of email addresses with in-depth content analysis and intelligent threat detection mechanisms. By integrating said various components, the method provides a robust solution to safeguard against a wide array of cybersecurity threats in email communications. The implementation of said method marks a significant advancement in the field of cybersecurity, addressing the evolving nature of cyber threats with a sophisticated and proactive approach.
Brief Description of the Drawings
[00026] The features and advantages of the present disclosure would be more clearly understood from the following description taken in conjunction with the accompanying drawings in which:
[00027] FIG. 1 represents an architecture of a system for an email address tracing to determine a cybersecurity threat, in accordance with the embodiments of the present disclosure.
[00028] FIG. 2 illustrates a flow diagram of a method for an email address tracing to determine a cybersecurity threat, in accordance with the embodiments of the present disclosure.
[00029] FIG. 3 illustrates a flow diagram of a method for an email address tracing to determine a cybersecurity threat, in accordance with the embodiments of the present disclosure.

Detailed Description
[00030] In the following detailed description of the invention, reference is made to the accompanying drawings that form a part hereof, and in which is shown, by way of illustration, specific embodiments in which the invention may be practiced. In the drawings, like numerals describe substantially similar components throughout the several views. These embodiments are described in sufficient detail to claim those skilled in the art to practice the invention. Other embodiments may be utilized and structural, logical, and electrical changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims and equivalents thereof.
[00031] The use of the terms “a” and “an” and “the” and “at least one” and similar referents in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The use of the term “at least one” followed by a list of one or more items (for example, “at least one of A and B”) is to be construed to mean one item selected from the listed items (A or B) or any combination of two or more of the listed items (A and B), unless otherwise indicated herein or clearly contradicted by context. The terms “comprising,” “having,” “including,” and “containing” are to be construed as open-ended terms (i.e., meaning “including, but not limited to,”) unless otherwise noted. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.
[00032] Pursuant to the "Detailed Description" section herein, whenever an element is explicitly associated with a specific numeral for the first time, such association shall be deemed consistent and applicable throughout the entirety of the "Detailed Description" section, unless otherwise expressly stated or contradicted by the context.
[00033] The present study pertains to the field of cybersecurity, more specifically to systems and methods for email address tracing as a means to enhance cybersecurity measures.
[00034] Embodiments of the present disclosure relate to a system 100 for tracing email addresses in order to ascertain potential cybersecurity threats. The system 100 comprises several modules, each designed to perform specific functions integral to the overall operation and effectiveness of the system in identifying and responding to cybersecurity threats.
[00035] According to a figurative elucidation of FIG. 1, showcasing an architectural composition of the system 100 that can comprise functional elements, yet not limited to an email tracing module 102, a data analysis module 104, a cybersecurity threat determination module 106 and an alert generation and response module 108. A person ordinarily skilled in art would prefer those elements or components of the system 100, to be functionally or operationally coupled with each other, in accordance with the embodiments of present disclosure.
[00036] In yet another embodiment, the first component of the system 100 is the email tracing module. Said module is responsible for tracing the email addresses involved in both incoming and outgoing emails. The primary function of said module is to monitor and record the email addresses from which emails are received and to which emails are sent. Said module plays a key role in gathering the initial data which forms the basis for further analysis.
[00037] In yet another embodiment, adjacent to the email tracing module is the data analysis module. Said module is tasked with the analysis of the traced email addresses from both incoming and outgoing emails. The analysis conducted by said module includes, but is not limited to, the assessment of sender and recipient information, IP addresses, and associated metadata. The sender information assessment involves scrutinizing details about the sender of an email, such as the sender's email address, while the recipient information assessment focuses on details pertaining to the recipient of the email. Said module also examines the IP addresses associated with the email, which can provide valuable information about the geographical origin of the email. The analysis of associated metadata includes, but is not limited to, examining the email headers for signs of email spoofing, such as discrepancies between the claimed origin and actual origin of the email.
[00038] In yet another embodiment, another key component of the system is the cybersecurity threat determination module. Said threat determination module is responsible for determining the presence of a cybersecurity threat. The threat determination module achieves said determination by comparing the data analyzed by the data analysis module with preconfigured data that serves as a benchmark for identifying potential threats. The preconfigured data may include known patterns of cybersecurity threats, profiles of previously identified malicious entities, and other relevant information that aids in the accurate identification of threats.
[00039] In a further embodiment, the system includes the alert generation and response module. Said module is activated if a cybersecurity threat is determined by the cybersecurity threat determination module. Upon activation, said module generates notifications to inform relevant personnel or systems of the identified threat. Additionally, said module may initiate action to counteract or mitigate the threat, such as blocking the sender's email address, alerting the IT security team, or initiating automated security protocols.
[00040] Further embodiments of the system include additional features that enhance the capability of the system. In an embodiment, the email tracing module is further configured to record the timestamp of each incoming and outgoing email. Said feature facilitates a chronological analysis of email traffic, which can be identifying patterns that may indicate a cybersecurity threat. The ability to analyze email traffic chronologically allows the system to detect anomalies in email patterns over time, such as sudden surges in email traffic from a particular source, which could be indicative of a cybersecurity threat.
[00041] In another embodiment, the data analysis module includes a feature for assessing the frequency of emails exchanged with particular email addresses. Said feature is designed to identify unusual patterns that could be indicative of a cybersecurity threat. For example, a sudden increase in the frequency of emails from a particular source, or a pattern of emails being sent at unusual times, could signal a potential security concern that warrants further investigation.
[00042] In an additional embodiment, said system focuses on the sender information assessment. In said embodiment, the assessment includes checking the sender's email address against a database of known malicious email addresses. Said feature enhances the system's ability to quickly identify emails from sources that have previously been associated with malicious activities, thereby enabling prompt action to be taken to mitigate potential threats.
[00043] In a further embodiment, the recipient information assessment includes evaluating the level of access and privileges of the recipient within an organization's network. Said feature is particularly useful in determining potential internal threats. By assessing the access level and privileges of the recipient, the system can identify situations where sensitive information may be at risk of being compromised from within the organization.
[00044] In a further embodiment, the system involves the IP address analysis including a geographical tracking feature. Said feature enables the system to flag emails originating from or sent to geographically suspicious locations. For example, if an email originates from a region known for harboring cybercriminals or from a location that is incongruent with the stated origin of the sender, the system can flag said email as a potential threat.
[00045] In a further embodiment, the associated metadata analysis includes examining email headers for signs of spoofing. Said examination involves looking for discrepancies between the claimed origin of the email and the actual origin as indicated by the email headers. Email spoofing is a common tactic used in phishing attacks and other malicious activities, making said feature an important tool in the system's arsenal for identifying potential cybersecurity threats.
[00046] In another embodiment, the cybersecurity threat determination module employs machine learning algorithms. Said

algorithms enable the module to continuously improve the accuracy of threat detection based on historical data. By learning from past incidents and patterns, the system becomes increasingly adept at identifying and responding to cybersecurity threats over time.
[00047] Referring to one or more preceding embodiments, the system, through the various modules and embodiments, offers a solution for tracing email addresses and determining cybersecurity threats. By analyzing a wide range of data, from sender and recipient information to IP addresses and email metadata, and by employing advanced techniques such as machine learning, the system provides an effective tool for organizations to safeguard their digital communications against a myriad of cybersecurity threats.
[00048] Referring to one or more preceding embodiments, the system relates to the technical domain of digital communication security, focusing on the identification, analysis, and management of cybersecurity threats that originate from or target email communications. Said system encompasses the development and utilization of advanced techniques for tracing both incoming and outgoing email addresses in order to detect, assess, and respond to potential cyber threats, such as phishing, malware distribution, and unauthorized data access.
[00049] Referring to one or more preceding embodiments, the scope of said system includes, but is not limited to, the utilization of data analysis algorithms, machine learning techniques, and integration with existing cybersecurity frameworks to provide a solution for safeguarding digital communication channels against a wide array of cyber threats. The Additionally, the system also covers the application of said techniques in various environments, including corporate networks, personal email systems, and cloud-based email services, thereby addressing a broad spectrum of cybersecurity challenges in modern digital communication systems.
[00050] The method 200 for tracing email addresses to determine cybersecurity threats involves a series of steps designed to identify and respond to various forms of cyber threats in email communications. The method integrates technologies and strategies to detect, analyze, and mitigate potential risks in email data traffic.
[00051] Referring to a pictorial depiction put forth in FIG. 2, representing a flow diagram of the method 200 that can comprise steps of, yet not restricted to (at step 202) tracing incoming and outgoing email addresses, (at step 204) analysing traced incoming and outgoing email addresses, (at step 206) determining cybersecurity threat, and (at step 208) generating notification and initiation of action. Said steps of the method 200 can be performed or executed, collectively or selectively, randomly or sequentially or in a combination thereof, in accordance with the embodiments of current disclosure.
[00052] In an embodiment, the first step involves the tracing of incoming and outgoing email addresses associated with emails. Said tracing establishes a baseline of regular communication patterns and identifying anomalous behavior. For instance, an increase in email traffic from unfamiliar sources might be indicative of a phishing campaign.
[00053] After tracing email addresses, the method involves analyzing said addresses to identify potential risks. Said analysis includes examining the frequency of emails, the nature of the email addresses (such as their domain names), and any patterns that might suggest malicious intent. For example, repeated emails from a domain known for spreading malware would be flagged for further investigation.
[00054] In an embodiment, the significance of the method lies in determining cybersecurity threats. Said determination is made by comparing the analyzed email address data against preconfigured threat criteria. Said criteria could include known malicious email addresses, patterns typical of phishing attacks, or other indicators of cybersecurity threats. By comparing incoming data against said criteria, the method can identify potential threats with a high degree of accuracy.
[00055] In an embodiment, upon identifying a potential cybersecurity threat, the method includes steps for generating notifications and initiating appropriate actions. Said steps might involve alerting IT personnel, automatically quarantining suspicious emails, or blocking email addresses deemed harmful.
[00056] In an embodiment, the enhancement to the basic method includes analyzing the content of emails for signs of social engineering or phishing. Said step of analysis involves a deeper inspection of the language and content of emails. Techniques such as natural language processing (NLP) can be used to detect anomalies in email content, such as urgent language, requests for sensitive information, or links to suspicious websites.
[00057] Referring to one or more preceding embodiments, said method 200 provides an approach to email security, addressing various facets of email communication and their potential exploitation by cyber threats. By integrating address tracing, data analysis, threat determination, and responsive actions, the method forms a robust defense mechanism against email-based cybersecurity threats. The addition of content analysis further enhances the ability to detect sophisticated social engineering and phishing attempts, ensuring a higher level of security in digital communications.
[00058] The disclosure discloses tracking and identifying email addresses. This system employs advanced techniques to analyze email headers, amalgamates data from diverse sources, and incorporates measures to safeguard user privacy. It overcomes the limitations of prior systems through its multifaceted components.
[00059] In the Data Acquisition Module, the extraction of information from email headers is performed. Extracted data includes the email address of the sender, IP addresses of routing servers, date and time stamps, and header metadata.
[00060] The Data Preprocessing Module performs cleansing and standardization of extracted data. It identifies any abnormalities or inconsistencies and prepares the data for subsequent analysis.
[00061] The Header Analysis Module utilizes machine learning techniques to scrutinize the language of email headers. By doing so, it reveals previously unrecognized patterns and insights, offering potential clues about the email sender.
[00062] The Multi-Source Data Integration Module is responsible for aggregating information from various sources, including social media profiles, public records, and previous email interactions. This integration forms a comprehensive profile of the email address owner.
[00063] By employing statistical analysis and machine learning, the Details Identification Module investigates the amalgamated information from header analysis and multi-source data integration. The investigation aims to ascertain and confirm details about the email address owner.
[00064] The Privacy-Preserving Module is designated to implement anonymization techniques. These techniques protect sensitive information prior to data integration and analysis.
[00065] The Reporting Module presents users with the ability to filter and search specific data. It displays identifying information about the email address owner in a clear and accessible manner. This comprehensive system, as detailed in the patent application, represents a significant advancement in email tracking and identification technology
[00066] The invention utilizing geolocation data to ascertain the geographical location of an email sender while obtaining relevant details in a manner that does not infringe upon user privacy. This system enhances incident response capabilities by swiftly addressing cybersecurity breaches and proactively identifying and tracking email addresses linked to security events. It strives to maintain a balance between efficient tracing and ethical data management practices, thereby upholding user privacy during the acquisition of email address information.
[00067] This email address tracing system integrates email addresses with geolocation data, social media profiles, and past behaviors to profile and identify individuals or organizations implicated in cybersecurity issues, aiding in the detection of potential threats. Utilizing machine learning techniques, the system alerts users or investigators to possible security risks by identifying anomalous email patterns and behaviors.
[00068] In conjunction with various email providers, the system offers a comprehensive solution for email investigations by reconstructing timelines, monitoring communication patterns, and extracting critical information. Its capability to seamlessly integrate with multiple email providers and domains extends the system's coverage across services and platforms.
[00069] The aim of this system is to enable the development of detailed profiles for digital forensics investigations. This is achieved by extracting forensic information such as IP addresses, timestamps, and client details from emails, thereby enhancing the profiling and identification of entities responsible for cybersecurity issues.
[00070] FIG. 3 illustrates a flow diagram of a method for an email address tracing to determine a cybersecurity threat, in accordance with the embodiments of the present disclosure.
[00071] Said flow diagram commences with a "Start" block, indicating the initiation of the process. Subsequent to this, "Email Address Validation" is performed, ensuring the authenticity of the email address in question. Thereafter, "IP Address Tracking" is engaged, which entails the monitoring and recording of the Internet Protocol address associated with the email address. Following this step, the "Identify ISP" block signifies the determination of the Internet Service Provider connected to the IP address. Proceeding further, the "Geographical Location" block is indicative of the derivation of the physical location based on the IP address. The next phase, "Request User Details," involves soliciting additional information pertaining to the user. Finally, "Display User Details" concludes the process, wherein the acquired user information is exhibited. This flowchart encapsulates the systematic approach employed by the system to trace email addresses and identify potential cybersecurity threats. The process is delineated in a structured manner, adhering to the formalities of patent application documentation.
[00072] Example embodiments herein have been described above with reference to block diagrams and flowchart illustrations of methods and apparatuses. It will be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by various means including hardware, software, firmware, and a combination thereof. For example, in one embodiment, each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations can be implemented by computer program instructions. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart block or blocks.
[00073] Throughout the present disclosure, the term ‘processing means’ or ‘microprocessor’ or ‘processor’ or ‘processors’ includes, but is not limited to, a general purpose processor (such as, for example, a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a microprocessor implementing other types of instruction sets, or a microprocessor implementing a combination of types of instruction sets) or a specialized processor (such as, for example, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), or a network processor).
[00074] The term “non-transitory storage device” or “storage” or “memory,” as used herein relates to a random access memory, read only memory and variants thereof, in which a computer can store data or software for any duration.
[00075] Operations in accordance with a variety of aspects of the disclosure is described above would not have to be performed in the precise order described. Rather, various steps can be handled in reverse order or simultaneously or not at all.
[00076] While several implementations have been described and illustrated herein, a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein may be utilized, and each of such variations and/or modifications is deemed to be within the scope of the implementations described herein. More generally, all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific implementations described herein. It is, therefore, to be understood that the foregoing implementations are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, implementations may be practiced otherwise than as specifically described and claimed. Implementations of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the scope of the present disclosure.

Claims
I/We Claim:
1. A system for an email address tracing to determine a cybersecurity threat, said system comprising:
an email tracing module traces incoming and outgoing email addresses of incoming and outgoing emails;
a data analysis module analyses traced incoming and outgoing email addresses of incoming and outgoing emails, wherein the analysis comprises assessment of a sender information and a recipient information, an IP addresses, and associated metadata;
a cybersecurity threat determination module determines cybersecurity threat based on comparison of analysed data and preconfigured data; and
an alert generation and response module generates notification and initiates action, if the cybersecurity threat is determined.
2. The system of claim 1, wherein the email tracing module is further configured to record the timestamp of each incoming and outgoing email, facilitating a chronological analysis of email traffic.
3. The system of claim 1, wherein the data analysis module includes a feature for assessing the frequency of emails exchanged with particular email addresses, to identify unusual patterns indicative of a cybersecurity threat.
4. The system of claim 1, wherein the sender information assessment includes checking the sender's email address against a database of known malicious email addresses.
5. The system of claim 1, wherein the recipient information assessment includes evaluating the level of access and privileges of the recipient within an organization's network, to determine potential internal threats.
6. The system of claim 1, wherein the IP address analysis includes a geographical tracking feature, where emails originating from or sent to geographically suspicious locations are flagged.
7. The system of claim 1, wherein the associated metadata analysis includes examining email headers for spoofing signs, such as discrepancies between claimed and actual origin servers.
8. The system of claim 1, wherein the cybersecurity threat determination module employs machine learning algorithms to continuously improve the accuracy of threat detection based on historical data.
9. A method for an email address tracing to determine a cybersecurity threat, said method comprising:
tracing incoming and outgoing email addresses of incoming and outgoing emails;
analysing traced incoming and outgoing email addresses of incoming and outgoing emails;
determining cybersecurity threat based on comparison of analysed data and preconfigured data; and
generating notification and initiates action, if the cybersecurity threat is determined.
10. The method of claim 9, wherein analysing the content of emails includes language and content analysis to detect indicators of social engineering or phishing attempts.

EMAIL ADDRESS TRACING FOR PROVIDING CYBERSECURITY
Abstract
The present study provides a system for tracing email addresses to determine cybersecurity threats. Said system includes an email tracing module for tracking both incoming and outgoing email addresses. A data analysis module is arranged for evaluating sender and recipient information, IP addresses, and associated metadata. The system includes a cybersecurity threat determination module that compares analyzed data with preconfigured criteria to identify potential threats. Upon detection of a threat, an alert generation and response module is activated, generating notifications and initiating appropriate action.
Fig. 1

, Claims:Claims
I/We Claim:
1. A system for an email address tracing to determine a cybersecurity threat, said system comprising:
an email tracing module traces incoming and outgoing email addresses of incoming and outgoing emails;
a data analysis module analyses traced incoming and outgoing email addresses of incoming and outgoing emails, wherein the analysis comprises assessment of a sender information and a recipient information, an IP addresses, and associated metadata;
a cybersecurity threat determination module determines cybersecurity threat based on comparison of analysed data and preconfigured data; and
an alert generation and response module generates notification and initiates action, if the cybersecurity threat is determined.
2. The system of claim 1, wherein the email tracing module is further configured to record the timestamp of each incoming and outgoing email, facilitating a chronological analysis of email traffic.
3. The system of claim 1, wherein the data analysis module includes a feature for assessing the frequency of emails exchanged with particular email addresses, to identify unusual patterns indicative of a cybersecurity threat.
4. The system of claim 1, wherein the sender information assessment includes checking the sender's email address against a database of known malicious email addresses.
5. The system of claim 1, wherein the recipient information assessment includes evaluating the level of access and privileges of the recipient within an organization's network, to determine potential internal threats.
6. The system of claim 1, wherein the IP address analysis includes a geographical tracking feature, where emails originating from or sent to geographically suspicious locations are flagged.
7. The system of claim 1, wherein the associated metadata analysis includes examining email headers for spoofing signs, such as discrepancies between claimed and actual origin servers.
8. The system of claim 1, wherein the cybersecurity threat determination module employs machine learning algorithms to continuously improve the accuracy of threat detection based on historical data.
9. A method for an email address tracing to determine a cybersecurity threat, said method comprising:
tracing incoming and outgoing email addresses of incoming and outgoing emails;
analysing traced incoming and outgoing email addresses of incoming and outgoing emails;
determining cybersecurity threat based on comparison of analysed data and preconfigured data; and
generating notification and initiates action, if the cybersecurity threat is determined.
10. The method of claim 9, wherein analysing the content of emails includes language and content analysis to detect indicators of social engineering or phishing attempts.