1. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet by providing a safe internet browsing by keeping internet service providers’ links’ clean from Malicious Attacks on the internet by building a protective layer at DNS level itself (prevent at the root) using artificial intelligence and machine learning technology.

2. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, wherein it provides bad IP addresses and bad domains based on their reputation using Artificial Intelligence and Machine Learning technology.

3. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, wherein to provide threat intelligence the invention has two components Intelligent Threat Vector API and Secure API are used.

4. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1 & 3, wherein the Intelligent Threat Vector API works on Artificial Intelligence and Machine Learning technology, that has predefined Malicious data of IP addresses and domains.

5. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, 3 & 4, wherein the ITV API prepares configuration according to open source network infrastructure components.

6. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, 3, 4 & 5 wherein the Secure API works on Artificial Intelligence and Machine Learning deals with live traffic inspection of Malicious data of IP addresses and domains.

7. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 2, wherein the artificial intelligence predicts the malicious domains and websites.

8. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 2 & 7, wherein during the training phase of machine learning it provides reference of good data and bad data

9. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, wherein a customized whatsapp integration is used to manage the incident, event, change and configuration.

10. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1 & 11, to ensure security of Whatsapp integration the present invention uses two factor authentication and reverse proxy multi-platform tunneling service.

11. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet substantially hereinbefore described.

DESC:FIELD OF INVENTION
4. This invention relates to a system and method of providing threat intelligence by providing a safe internet browsing by keeping internet service providers’ links’ clean from malicious cyber attacks by building a protective layers at DNS level itself by using artificial intelligence.

BACKGROUND OR PRIOR ART
5. Firewalls are now an integral part of network security. An intelligent firewall that prevents unauthorized access to a system has been developed. Artificial intelligence applications are uniquely suited for the ever-changing, ever-evolving world of network security. Typical firewalls are only as good as the information provided by the Network Administrator. A new type of attack creates vulnerabilities, which a static firewall does not have the ability to avoid without human direction. An AI managed firewall service, however, can protect a computer network from known and future threats. The smart detection engine will aim at not only detecting anomalous network traffic as in classical IDSs, but also detecting unusual structures data packets that suggest the presence of virus data.

The traditional firewall used in a computing device is becoming less protective for the recent threats happening around. In fact, it might also be a huge pathway into the enterprise leaving it completely unprotected, which is populated by unrestricted DNS information. This has become a conduit of choice for cyber criminals looking to enter your network. The present invention is developed with a scope to provide safe internet browsing in a computing device by keeping internet service providers’ links’ clean from Malicious Attacks on the internet by building a protective layer at DNS level itself (prevent at the root). The present invention is a solution to keep all advanced persistent threats away for business or personal network with its defensive function based on threat vector intelligence, information categories and countries (IP blocks) and it’s based on DNS Firewall with Automation and machine learning technology.
The present invention as an Internet Security Solution. This protects the infrastructure from all the cyber attacks at the root of the internet itself. This Security Solution can be implemented in Public Cloud, Private Cloud / On premises, Shared Public Cloud.

6. The internet security mechanism provided by firewall (traditional and artificial intelligence) are known to have been provided in the art, which are discussed below:

US 14/163,186
Methods, systems, and apparatuses for proactively protecting a computing network are disclosed. A proactive security mechanism is disclosed, among other things, with the ability to monitor a protected domain in real-time and safely identify inoculation procedures for responding to threats introduced) to the protected domain via malware. The proactive security mechanism includes an Artificial Neural Network Interface (ANNI) configured to execute at least some features of the proactive security mechanism.

US13/954,860
Evaluating a potentially malicious sample using a copy-on-write overlay is disclosed. A first virtual machine instance is initialized as a copy-on-write overlay associated with an original virtual machine image. The first virtual machine image is started and a first sample is executed. A second virtual machine instance is initialized as a copy-on-write overlay associated with a second original virtual machine image. The second virtual machine image is started and a second sample is executed. The first and second samples are executed at an overlapping time.

US 9,264,397 B2A
The number of computing devices associated with a particular user have a network capability between them for management and control, said capability to enable these devices, running on different, physically distributed hardware, to interwork securely and privately.

The present invention differs from the above mentioned prior-arts as it provides bad IP addresses and bad domains based on their reputation using Artificial Intelligence and Machine Learning technology. To provide threat intelligence the present invention has two components (i.e.,) Intelligent Threat Vector API and Secure API. These APIs are part of the present invention and will remain with the applicant. The present invention also provides a customized whatsapp integration which is used to manage the incident, event, change and configuration.

7. Difference between TRADTIONAL FIREWALL AND THE PRESENT INVENTION (MENTIONED AS DIMA IN THE BELOW TABLE)

OBJECT OF THE INVENTION
The primary object of the present invention is to provide a threat intelligence mechanism of internet security and the hardware that implements by actively identifying new malicious attacks.

The another object of the present invention is to provide bad IP addresses and bad domains based on their reputation using Artificial Intelligence and Machine Learning technology. To provide threat intelligence we have two components in our corporate public cloud (i.e.,) Intelligent Threat Vector API and Secure API. These APIs are part of the present invention and will remain only in the applicant’s Corporate Cloud.

The another object of the present invention to detect malware, command and control, bots etc., by an in-depth analysis of layer 7 parameter.

The another object of the present invention is to provide the prediction of 74 threat information categories using Artificial Intelligence.

The another object of the present invention is to provide a customized whatsapp integration which is used to manage the incident, event, change and configuration.

DETAILED DESCRIPTION OF THE INVENTION
The present invention discloses a mechanism of providing threat intelligence by providing a safe internet browsing by keeping internet service providers’ links’ clean from Malicious Attacks on the internet by building a protective layer at DNS level itself (prevent at the root).

Our Intelligent Threat Vector API works on Artificial Intelligence and Machine Learning technology that has predefined malicious data of IP addresses and domains. Our ITV API prepares configuration according to open source network infrastructure components. Our Secure API which is also working on Artificial Intelligence and Machine Learning deals with live traffic inspection of malicious data of IP addresses and domains.

Our invention has the access control lists and databases. The access control list inspects the IP addresses from DNS queries. Databases inspect the IP addresses and domains from DNS queries which has 6 databases - White list, black list, black hole, AI threat, AI information categories & our ITV database. Our Corporate Public Cloud has the ITV and Secure API connects to our firewall. Our ITV connects to access control lists and ITV database. Our Secure API connects to the black hole database, AI Threat database, AI information category database. The whitelist and blacklist database are integrated with whatsapp applications. Using Whatsapp application incident, event, change, configuration can be managed. Access control takes care of forwarding traffic, while the database takes care of returning traffic.

The Black hole Database has the Malicious IP addresses information received from our Secure API. The purpose of Black hole Database is to collect the malicious IP addresses based on the IP addresses’ spam score and reputation. This also works on Artificial Intelligence and Machine Learning.

The AI threat database uses domain and page authority automation. AI information category database use keyword data sets automation. AI threat database uses the automation results of domain and page authority from where Machine learning is performed. AI information category database use the automation results of keyword data sets from where Machine learning is performed. The resulting truth table is used for the prediction algorithm.

Artificial intelligence prediction of malicious domains and websites. During the training phase of machine learning we provide reference of good data and bad data. The good and bad data provided is predefined. The resulting good data truth table and bad data truth table is stored in the memory. The reference data or test data truth table is built as input to the AI prediction engine. The AI prediction algorithm runs over test data, good and bad truth tables, with this the result of the AI prediction algorithm is decided.

Artificial intelligence prediction of information categories. During the training phase of machine learning 74 information categories data sets are used in the form of truth tables, which generates 74 truth tables which is stored in the memory. The reference test data truth table is given as input to the AI prediction engine. Now the AI prediction algorithm runs over predefined 74 truth tables and the test data truth table, with this the result of the AI prediction algorithm is decided.

There are possibilities for our firewall to go to a failed state when it receives a misleading configuration from our Intelligent Threat Vector. To ensure the continuous service of our firewall an intelligent algorithm is written within our invention to predict the failed state and roll back to the last known good configuration. For example: If the our invention fails at 3AM due to misleading configuration from our ITV, the intelligent algorithm predicts the failure and rolls back to the last known good configuration at 2am. So we ensure continuous service of firewall.

Whatsapp integration of our invention is a customized solution. Incident, event, change and configuration management is achieved through the whatsapp application. To ensure security of Whatsapp integration we have enabled two factor authentication and reverse proxy multi-platform tunneling service.

CLAIMS
We claim,
1. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet by providing a safe internet browsing by keeping internet service providers’ links’ clean from Malicious Attacks on the internet by building a protective layer at DNS level itself (prevent at the root) using artificial intelligence and machine learning technology.

2. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, wherein it provides bad IP addresses and bad domains based on their reputation using Artificial Intelligence and Machine Learning technology.

3. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, wherein to provide threat intelligence the invention has two components Intelligent Threat Vector API and Secure API are used.

4. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1 & 3, wherein the Intelligent Threat Vector API works on Artificial Intelligence and Machine Learning technology, that has predefined Malicious data of IP addresses and domains.

5. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, 3 & 4, wherein the ITV API prepares configuration according to open source network infrastructure components.

6. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, 3, 4 & 5 wherein the Secure API works on Artificial Intelligence and Machine Learning deals with live traffic inspection of Malicious data of IP addresses and domains.

7. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 2, wherein the artificial intelligence predicts the malicious domains and websites.

8. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 2 & 7, wherein during the training phase of machine learning it provides reference of good data and bad data

9. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, wherein a customized whatsapp integration is used to manage the incident, event, change and configuration.

10. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1 & 11, to ensure security of Whatsapp integration the present invention uses two factor authentication and reverse proxy multi-platform tunneling service.

11. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet substantially hereinbefore described.

,CLAIMS:CLAIMS
We claim,
1. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet by providing a safe internet browsing by keeping internet service providers’ links’ clean from Malicious Attacks on the internet by building a protective layer at DNS level itself (prevent at the root) using artificial intelligence and machine learning technology.

2. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, wherein it provides bad IP addresses and bad domains based on their reputation using Artificial Intelligence and Machine Learning technology.

3. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, wherein to provide threat intelligence the invention has two components Intelligent Threat Vector API and Secure API are used.

4. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1 & 3, wherein the Intelligent Threat Vector API works on Artificial Intelligence and Machine Learning technology, that has predefined Malicious data of IP addresses and domains.

5. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, 3 & 4, wherein the ITV API prepares configuration according to open source network infrastructure components.

6. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, 3, 4 & 5 wherein the Secure API works on Artificial Intelligence and Machine Learning deals with live traffic inspection of Malicious data of IP addresses and domains.

7. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 2, wherein the artificial intelligence predicts the malicious domains and websites.

8. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 2 & 7, wherein during the training phase of machine learning it provides reference of good data and bad data

9. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1, wherein a customized whatsapp integration is used to manage the incident, event, change and configuration.

10. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet as claimed in claim 1 & 11, to ensure security of Whatsapp integration the present invention uses two factor authentication and reverse proxy multi-platform tunneling service.

11. A System and method for building a protective layer at DNS level for cyber Attacks on the Internet substantially hereinbefore described.