NXP Semiconductors had 63 patents in cybersecurity during Q2 2024. The patents filed by NXP Semiconductors NV in Q2 2024 cover a range of technologies including protecting Machine Learning models from extraction, communicating data for authentication and location determination, priority encoded domains in an SoC, elliptic curve cryptography authentication method, and audio stream sharing via a wireless link between audio source and sink devices. These patents focus on enhancing security, communication, and processing capabilities in various electronic devices. GlobalData’s report on NXP Semiconductors gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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NXP Semiconductors had no grants in cybersecurity as a theme in Q2 2024.
Recent Patents
Application: Method and system for protecting a machine learning model against extraction (Patent ID: US20240202323A1)
The patent by NXP Semiconductors NV describes systems and methods for protecting a Machine Learning (ML) model from extraction. The method involves obtaining input samples for inference operations, detecting temporal inconsistencies among the input samples or outputs, and identifying attempts to extract the ML model based on these inconsistencies. Responsive actions can be taken, such as informing a back-end service of an attack, reducing accuracy or speed of inference operations, or returning random outputs. The system includes a processor and memory to deploy the ML model, detect temporal inconsistencies, and identify extraction attempts based on these inconsistencies. The hardware memory contains program instructions for obtaining input samples, detecting inconsistencies, and determining extraction attempts based on the inconsistencies.
The method and system focus on detecting temporal inconsistencies in input samples or outputs of an ML model to identify potential extraction attempts. By estimating motion of pixels or objects and determining differences between successive samples or outputs, the system can detect anomalies that indicate an ongoing extraction attempt. Responsive actions can be taken to mitigate the threat, such as informing relevant services, reducing accuracy or speed of operations, or returning random outputs. The hardware memory contains program instructions for implementing these detection and response mechanisms, providing a comprehensive solution for protecting ML models from unauthorized extraction.
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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.
