BMC Software had four patents in cybersecurity during Q2 2024. BMC Software Inc has developed systems and techniques for efficiently detecting anomalous behaviors of monitored objects by using multiple hashing algorithms to generate unique hash signatures and aggregating metric values within hash bins. Machine learning models are then trained using these signatures and metric values to identify anomalous objects during subsequent scoring. GlobalData’s report on BMC Software gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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BMC Software had no grants in cybersecurity as a theme in Q2 2024.
Recent Patents
Application: Anomaly detection using hash signature generation for model-based scoring (Patent ID: US20240112071A1)
The patent filed by BMC Software Inc. describes systems and techniques for efficiently detecting anomalous behaviors of monitored objects. By using multiple hashing algorithms to generate unique hash signatures for each object and aggregating metric values within hash bins, machine learning models can be trained to score these aggregated metric values and identify anomalous objects. The claims detail the computer program product, method, and system for implementing this process, including receiving metric values, accessing hash signatures, scoring aggregated metric values against machine learning models, and identifying anomalous objects based on the scores obtained. The claims also cover additional features such as using multiple hashing algorithms, training the machine learning model, and aggregating training metric values within hash bins.
Overall, the patent focuses on a comprehensive approach to anomaly detection by combining hashing algorithms, machine learning models, and aggregated metric values to efficiently identify anomalous objects among monitored entities. The claims provide a detailed outline of the steps involved in implementing this process, including scoring, identifying anomalous objects, and utilizing multiple hashing algorithms to generate unique hash signatures. The patent aims to provide a fast, efficient, and cost-effective solution for detecting anomalies in monitored objects, particularly in the context of IT landscapes where Key Performance Indicators (KPIs) are crucial metrics.
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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.
