Nozomi Networks had four patents in artificial intelligence during Q2 2024. The patent filed by Nozomi Networks Inc in Q2 2024 describes a method for detecting anomalies in data traffic from peripheral devices that mimic human-like patterns. This method involves retrieving data packets, identifying data communications, parsing content to extract communication features, classifying features using absolute and majority classifiers, and flagging anomalies when classified as malicious. GlobalData’s report on Nozomi Networks gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Nozomi Networks had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Method for detecting anomalies in data traffic generated by peripheral devices simulating human-like patterns (Patent ID: US20240179163A1)
The patent filed by Nozomi Networks Inc. describes a method for detecting anomalies in data traffic generated by peripheral devices that mimic human-like patterns. The method involves retrieving data packets sent by a peripheral device to a computer, identifying data communications within a specific timeframe, parsing the content of the data packets to extract communication features, classifying these features using absolute and majority classifiers, and signaling an anomaly if the classifiers determine the communication to be malicious. The classifiers include deny list, neural network, key release speed, inconsistent code, typing speed, transition matrix, and typing speed distribution classifiers, each focusing on specific communication features to identify anomalies.
The method outlined in the patent involves a comprehensive approach to detecting anomalies in data traffic from peripheral devices by analyzing various communication features such as words, key combinations, timestamps, key release speed, key code, typing speed, key transition speed, and typing speed distribution. By utilizing a combination of absolute and majority classifiers, the system can effectively identify malicious data communications based on predefined thresholds and patterns. This method can be particularly useful in identifying and preventing cybersecurity threats that may attempt to mimic human-like behavior to evade detection, providing enhanced security measures for computer systems against potential attacks.
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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.
