18498379. SYSTEM FOR SOFTWARE CODE CYBER SECURITY BASED ON MACHINE LEARNING VULNERABILITY DETECTION AND GENERATION AND IMPLEMENTATION OF VULNERABILITY TEST (BANK OF AMERICA CORPORATION)
SYSTEM FOR SOFTWARE CODE CYBER SECURITY BASED ON MACHINE LEARNING VULNERABILITY DETECTION AND GENERATION AND IMPLEMENTATION OF VULNERABILITY TEST
Organization Name
Inventor(s)
Panduranga Dongle of Hyderabad IN
John Iruvanti of Bhadradri Kothagudem IN
Komuraiah Kannaveni of Hyderabad IN
SYSTEM FOR SOFTWARE CODE CYBER SECURITY BASED ON MACHINE LEARNING VULNERABILITY DETECTION AND GENERATION AND IMPLEMENTATION OF VULNERABILITY TEST
This abstract first appeared for US patent application 18498379 titled 'SYSTEM FOR SOFTWARE CODE CYBER SECURITY BASED ON MACHINE LEARNING VULNERABILITY DETECTION AND GENERATION AND IMPLEMENTATION OF VULNERABILITY TEST
Original Abstract Submitted
An end-to-end approach for (i) identifying potential vulnerabilities in software applications, including security vulnerabilities, (ii) verifying/confirming the potential vulnerabilities as actual vulnerabilities and (iii) in response, identifying the necessary remedial actions necessary to eliminate or at least mitigate the vulnerabilities. An intelligent agent is implemented that is configured to detect a change to the application's code or computing environment and, as a result of detection of changes to the code or computing environment, identify potential vulnerabilities, verify/confirm the potential vulnerabilities as actual vulnerabilities through determination/creation of vulnerability test cases and automatically identify the necessary remedial actions necessary to eliminate or mitigate the vulnerabilities.
