Rubrik had 11 patents in cybersecurity during Q1 2024. Rubrik Inc filed patents related to implementing a scalable automated training framework for anomaly and ransomware detection, real-time detection of ransomware and system threats, cloud object storage and versioning system, establishing secure connectivity for data management systems, and facilitating snapshot exports between different cloud environments. These patents focus on improving data management, security, and efficiency in cloud computing environments. GlobalData’s report on Rubrik gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Rubrik grant share with cybersecurity as a theme is 45% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Scalable automated training framework (Patent ID: US20240089282A1)
Rubrik Inc. has developed a patent for a scalable automated training framework for anomaly and ransomware detection. The system involves instantiating virtual machines with corresponding file systems, simulating user actions and ransomware on these machines to generate metadata files based on snapshots of the changes, and training a ransomware detection model using machine learning algorithms and training data derived from the metadata files. The method includes executing a computer program to simulate user actions and malware presence, generating training data based on these simulations, and training a machine learning model for malware detection.
The patent claims detail the method further, including training the model for specific types of malware, obtaining snapshots of virtual machines to track changes, simulating user actions like interface manipulation and resource navigation, and detecting malware presence on virtual machines or other computing devices. The apparatus and non-transitory computer-readable medium described in the claims outline the hardware components and storage requirements for executing the method, emphasizing the importance of simulating user actions and malware presence to generate training data for effective malware detection using machine learning models.
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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.
