Patents by Inventor Jonathan Moshe MONSONEGO

Jonathan Moshe MONSONEGO 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: 11074341
    Abstract: Cybersecurity peer identification (CPI) technology obtains security group definitions from an identity directory, computes peerSimilarityScores that represent user similarity in terms of security permissions, and submits contextual cybersecurity peer data to cybersecurity peer-based functionality (CPBF). CPBF code may then perform behavior analytics, resource management, permissions management, or location management. Cyberattacks may then be disrupted or mitigated, and inefficiencies may be avoided or decreased. Having smaller security groups in common gives users higher peerSimilarityScores than having larger groups in common, as a result of logarithmic, reciprocal, or other score functions. Security group definitions are refreshed and peer scores are updated at regular intervals or on demand by CPI code, to avoid staleness.
    Type: Grant
    Filed: February 10, 2019
    Date of Patent: July 27, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Jonathan Moshe Monsonego, Itay Argoeti, Amir Harar
  • Publication number: 20210120014
    Abstract: Techniques for user impact potential based security alert management in computer systems are disclosed. One example technique includes receiving an alert indicating that a security rule has been violated by a user. The example technique can also include, in response to receiving the data representing the alert, determining an impact score of the user based on the profile of the user. The impact score represents a deviation of an assigned value to the profile of the user and a mean value of assigned values of profiles of all users in the organization. The example technique can further include calculating a ranking value of the alert in relation to other alerts based on the determine impact score and other impacts scores corresponding to the other alerts and selectively surfacing the alert to a system analyst based on the calculated ranking value in relation to other alerts.
    Type: Application
    Filed: October 22, 2019
    Publication date: April 22, 2021
    Inventors: Itay Argoety, Jonathan Moshe Monsonego, Idan Hen, Payal Rani, Sridhar Periyasamy
  • Publication number: 20200274894
    Abstract: A machine learning model is trained using tuples that identify an actor, a resource, and a rating based on a normalized count of the actor's attempts to access the resource. Actors may be users, groups, IP addresses, or otherwise defined. Resources may be storage, virtual machines, APIs, or otherwise defined. A risk assessor code feeds an actor—resource pair to the trained model, which computes a recommendation score using collaborative filtering. The risk assessor inverts the recommendation score to obtain a risk measurement; a low recommendation score corresponds to a high risk, and vice versa. The risk assessor code or other code takes cybersecurity action based on the recommendation score. Code may accept a risk R, or aid mitigation of the risk R, where R denotes a risk that the scored pair represents an unauthorized attempt by the pair actor to access the pair resource.
    Type: Application
    Filed: February 27, 2019
    Publication date: August 27, 2020
    Inventors: Itay ARGOETI, Roy LEVIN, Jonathan Moshe MONSONEGO
  • Publication number: 20200257797
    Abstract: Cybersecurity peer identification (CPI) technology obtains security group definitions from an identity directory, computes peerSimilarityScores that represent user similarity in terms of security permissions, and submits contextual cybersecurity peer data to cybersecurity peer-based functionality (CPBF). CPBF code may then perform behavior analytics, resource management, permissions management, or location management. Cyberattacks may then be disrupted or mitigated, and inefficiencies may be avoided or decreased. Having smaller security groups in common gives users higher peerSimilarityScores than having larger groups in common, as a result of logarithmic, reciprocal, or other score functions. Security group definitions are refreshed and peer scores are updated at regular intervals or on demand by CPI code, to avoid staleness.
    Type: Application
    Filed: February 10, 2019
    Publication date: August 13, 2020
    Inventors: Jonathan Moshe MONSONEGO, Itay ARGOETI, Amir HARAR