NVIDIA had 43 patents in cybersecurity during Q1 2024. The patents filed by NVIDIA Corp in Q1 2024 include technologies for generating a 3D GUI dashboard to display network anomalies, techniques for detecting EM fault injection attacks, generating unsupervised behavior models for anomaly detection, transmitting configuration information wirelessly, and improving landmark detection using an iterative neural network to reduce jitter in video results. GlobalData’s report on NVIDIA gives a 360-degree view of the company including its patenting strategy. Buy the report here.
NVIDIA grant share with cybersecurity as a theme is 30% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Visualization technology for finding anomalous patterns (Patent ID: US20240106848A1)
The patent filed by NVIDIA Corp. describes technologies for generating a graphical user interface (GUI) dashboard with a 3D grid of unit cells to visualize anomaly statistics for network access events. The system accesses a dataset, determines anomaly statistics for network addresses, sorts them based on these statistics, and generates a gridded data set with unit cells representing composite anomaly scores. The GUI dashboard displays this data with rows for network addresses, columns for time intervals, colors indicating anomaly scores, and column heights representing the number of network access events, providing a visual representation of anomalous patterns in real-time or historical records.
The computing system outlined in the patent includes memory and processing devices to execute operations such as accessing datasets, determining anomaly statistics, sorting network addresses, and generating a 3D grid of unit cells based on anomaly scores. The system allows for customization through default settings, user input modifications, and interactive features like panning, zooming, and tilting. Additionally, the system can display area charts to visualize the magnitude of network access events over time intervals. Overall, the technology enables the creation of a GUI dashboard that efficiently identifies and represents anomalous patterns in network access events, offering a comprehensive tool for monitoring and analyzing network security.
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