Patents by Inventor Or Soffer

Or Soffer 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).

  • SYSTEM AND METHOD FOR COMPUTER NETWORKS ENDPOINT THREAT PREDICTION BASED ON VECTOR EMBEDDING
    Publication number: 20250088526
    Abstract: Systems and methods of detecting communication anomalies in a computer network, including: analyzing sampled traffic within the computer network, to identify at least one entity in the computer network, generating a network graph that corresponds to the computer network, wherein the network graph includes a plurality of nodes based on the identified at least one entity, training a deep learning (DL) algorithm to generate at least one vector characterizing the behavior of each entity in the computer network based on the generated network graph, applying the trained DL algorithm on the sampled traffic, to predict the probability of a communication in the sampled traffic, wherein the prediction is based on the generated at least one vector, and detecting an anomaly when the predicted probability is below an anomaly threshold.
    Type: Application
    Filed: November 21, 2024
    Publication date: March 13, 2025
    Applicant: TWEENZNET LTD.
    Inventors: Aviv YEHEZKEL, Eyal ELYASHIV, Or SOFFER
  • SYSTEM AND METHOD FOR COMPUTER NETWORKS ENDPOINT THREAT PREDICTION BASED ON VECTOR EMBEDDING
    Publication number: 20230090205
    Abstract: Systems and methods of detecting communication anomalies in a computer network, including: analyzing sampled traffic within the computer network, to identify at least one entity in the computer network, generating a network graph that corresponds to the computer network, wherein the network graph includes a plurality of nodes based on the identified at least one entity, training a deep learning (DL) algorithm to generate at least one vector characterizing the behavior of each entity in the computer network based on the generated network graph, applying the trained DL algorithm on the sampled traffic, to predict the probability of a communication in the sampled traffic, wherein the prediction is based on the generated at least one vector, and detecting an anomaly when the predicted probability is below an anomaly threshold.
    Type: Application
    Filed: September 19, 2022
    Publication date: March 23, 2023
    Applicant: TWEENZNET LTD.
    Inventors: Aviv YEHEZKEL, Eyal Elyashiv, Or Soffer