ForeScout Technologies had three patents in artificial intelligence during Q2 2024. ForeScout Technologies Inc’s patents in Q2 2024 focus on classification and clustering technologies. The classification methods involve accessing multiple device classification methods with varying reliability levels, using higher reliability models to train or tune lower reliability models. The clustering method involves determining clusters of network entities based on behavior and identifying anomalies within the network based on these clusters. 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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ForeScout Technologies had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Self-training classification (Patent ID: US20240195815A1)
The patent filed by ForeScout Technologies Inc. describes systems and methods for device classification using multiple classification methods with associated models and reliability levels. The higher reliability classification methods are used to train or tune the models associated with lower reliability methods, improving the accuracy of device classification on a network. The method involves accessing a variety of device classification methods, generating data sets based on classifying devices on the network, and selecting the most reliable methods for classification.
The system described in the patent includes a processing device and memory to access and generate data sets for device classification methods, select the most reliable methods, and perform initial classification of devices on the network. The processing device can also determine tuning data sets, tune classification models, and store the tuned models for future use. Additionally, the system can adjust the reliability levels of classification methods based on classification results and perform classification using the selected methods. The patent also covers a non-transitory computer-readable medium with instructions for determining usable classification methods based on initial classification, generating data sets, and tuning models based on reliability levels, ultimately improving the accuracy and efficiency of device classification in a network environment.
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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.
