Patents by Inventor Hemant Meenanath Patil

Hemant Meenanath Patil has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 12019749
    Abstract: Systems, methods, and apparatus are provided for intelligent cybersecurity processing of a product update. A fetcher application may access an updated version of a software product, a prior version of the product, and a version control system for the product. A malicious software identification engine may process the data using batch or stream processing to identify suspect code and metadata anomalies in the updated version. The engine may decompile executable binary code to obtain source code for the updated version and the prior version. A machine learning engine may receive input from the malicious software identification engine and classify the input using an NER-based machine learning model. Based on output from the machine learning engine, a control dashboard may block installation of a malicious product update.
    Type: Grant
    Filed: February 10, 2022
    Date of Patent: June 25, 2024
    Assignee: Bank of America Corporation
    Inventors: Pallavi Yerra, Ra Uf Ridzuan Bin Ma Arof, Surendran, Hemant Meenanath Patil
  • Patent number: 11934531
    Abstract: An apparatus includes a memory and a processor. The memory stores descriptions of known vulnerabilities and information generated by a monitoring subsystem. Each description of a known vulnerability identifies software components that are associated with the known vulnerability. The monitoring subsystem monitors software programs that are installed within a computer system. The information includes descriptions of issues that are associated with the software programs. The processor generates a set of mappings, based on a comparison between the text describing the known software vulnerabilities and the text describing the issues. Each mapping associates a software program that is associated with an issue with a known software vulnerability. The processor also uses a machine learning algorithm to predict that a given software program is associated with a particular software vulnerability.
    Type: Grant
    Filed: February 25, 2021
    Date of Patent: March 19, 2024
    Assignee: Bank of America Corporation
    Inventors: Benjamin John Ansell, Yuvraj Singh, Min Cao, Ra Uf Ridzuan Bin Ma Arof, Hemant Meenanath Patil, Pallavi Yerra, Kaushik Mitra Chowdhury
  • Publication number: 20230252152
    Abstract: Systems, methods, and apparatus are provided for intelligent cybersecurity processing of a product update. A fetcher application may access an updated version of a software product, a prior version of the product, and a version control system for the product. A malicious software identification engine may process the data using batch or stream processing to identify suspect code and metadata anomalies in the updated version. The engine may decompile executable binary code to obtain source code for the updated version and the prior version. A machine learning engine may receive input from the malicious software identification engine and classify the input using an NER-based machine learning model. Based on output from the machine learning engine, a control dashboard may block installation of a malicious product update.
    Type: Application
    Filed: February 10, 2022
    Publication date: August 10, 2023
    Inventors: Pallavi Yerra, Ra Uf Ridzuan Bin Ma Arof, . Surendran, Hemant Meenanath Patil
  • Publication number: 20220269791
    Abstract: An apparatus includes a memory and a processor. The memory stores descriptions of known vulnerabilities and information generated by a monitoring subsystem. Each description of a known vulnerability identifies software components that are associated with the known vulnerability. The monitoring subsystem monitors software programs that are installed within a computer system. The information includes descriptions of issues that are associated with the software programs. The processor generates a set of mappings, based on a comparison between the text describing the known software vulnerabilities and the text describing the issues. Each mapping associates a software program that is associated with an issue with a known software vulnerability. The processor also uses a machine learning algorithm to predict that a given software program is associated with a particular software vulnerability.
    Type: Application
    Filed: February 25, 2021
    Publication date: August 25, 2022
    Inventors: Benjamin John Ansell, Yuvraj Singh, Min Cao, Ra Uf Ridzuan Bin Ma Arof, Hemant Meenanath Patil, Pallavi Yerra, Kaushik Mitra Chowdhury