ForeScout Technologies has been granted a patent for a method to detect anomalous behavior in data traffic on a network. The method involves parsing data traffic, deriving attribute values, selecting models, updating models, assessing compliance with security policies, and generating alerts for policy violations. GlobalData’s report on ForeScout Technologies gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on ForeScout Technologies, was a key innovation area identified from patents. ForeScout Technologies's grant share as of April 2024 was 43%. Grant share is based on the ratio of number of grants to total number of patents.
Detecting anomalous behavior in data traffic on a network
A recently granted patent (Publication Number: US11949704B2) outlines a method for detecting anomalous behavior in data traffic on a data communication network. The method involves parsing data traffic to extract protocol field values, deriving attribute values of hosts and links, selecting models based on these attributes, and updating them accordingly. The models are assessed against attribute-based policies to ensure network security, with alert signals generated if violations are detected. The patent also details the use of classifiers and heuristics to derive attribute values, as well as the creation of rules and policies to streamline the detection process.
Furthermore, the patent describes an intrusion detection system, a data communication network, and an apparatus implementing the method. These systems are designed to parse data traffic, extract protocol field values, derive attribute values, select models, update them, and assess compliance with attribute-based policies to ensure network security. The systems are equipped to generate alert signals in case of policy violations, providing a comprehensive approach to detecting and responding to anomalous behavior in data traffic. The patent also introduces the concept of a quarantine for hosts or links without available models, storing attribute values and hypotheses to aid in decision-making regarding their legitimacy or malicious intent.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
