MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202641089066 A) filed by Mr. S. Noor Mohammed; Gabriella Smriti S; Akshaya E; Priyadharshini K; Asin Stany A; and Jayasneha D S on July 22, 2026, for Novel System, Design And Method Of Hybrid Framework For Adaptive Intrusion Detection And Automated Digital Forensic Evidence Correlation In Automotive Systems.
Inventors include Mr. S. Noor Mohammed; Gabriella Smriti S; Akshaya E; Priyadharshini K; Asin Stany A; and Jayasneha D S.
The application for the patent was published on July 31, 2026, under issue no. 31/2026.
Abstract: 6. ABSTRACT OF THE INVENTION The patent disclosure covers Novel System, Design and Method of Hybrid Framework for Adaptive Intrusion Detection and Automated Digital Forensic Evidence Correlation in Automotive Systems. Intelligent and quick security measures are desperately needed since modern connected cars are more susceptible to sophisticated cyberattacks that target in-car networks, electronic control units (ECUs), and connected services. Artificial intelligence, anomaly detection, signature-based analysis, and automated forensic investigation are all combined into a single security architecture in this patent's Hybrid Framework for Adaptive Intrusion Detection and Automated Digital Forensic Evidence Correlation in Automotive Systems. In order to detect known and unknown assaults with high accuracy and few false alarms, the framework continuously monitors communication protocols like CAN, Automotive Ethernet, and diagnostic interfaces. It does this by dynamically adjusting detection models. The patent automatically gathers, stores, correlates, and ranks digital forensic evidence from various automotive components, such as ECUs, network logs, sensor data, and event records, upon detecting suspicious activity. It does this while preserving the integrity of the evidence through secure timestamping and cryptographic verification. Correlation algorithms powered by machine learning rebuild attack patterns, identify compromised components, and give investigators thorough incident histories for quick investigation. The adaptive design makes it possible to continuously learn from fresh assault patterns, enhancing resistance to changing cyberthreats. The patent greatly shortens incident response times, boosts cyber resilience, facilitates regulatory compliance, and increases the dependability, safety, and credibility of software-defined and connected automotive systems by combining real-time intrusion detection with automated forensic evidence correlation.
Disclaimer: Curated by HT Syndication.
