MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641075951 A) filed by Peri College Of Arts And Science on June 19, 2026, for An Intelligent Intrusion Detection And Prevention System For Lo T Environment.

Inventors include Govarthanan G; Dr. Yogeshwari M; Yuvalakshmi M; Rajeshwari R; Alsiya Fathima A; and Asma A.

The application for the patent was published on July 03, 2026, under issue no. 27/2026.

Abstract: The present invention relates to an Inte!Iigent Intrusion Detection and Prevention System (IIDPS) for Internet of Things (loT) environment that detects, predicts and mitigates cyber threats in real-time using a hybrid artificial intelligence framework. The proposed system includes edge intelligence, federated learning, digital twin simulation, blockchain-based threat intelligence sharing and autonomous response orchestration to protect heterogeneous loT networks. The invention relies on distributed anomaly detection models deployed on edge nodes to detect unknown attacks, zero-day exploits, botnets, ·device spoofing, ransomware propagation and abnormal network behavior, as opposed to conventional approaches that are based on centralized monitoring and signatures. A digital twin environment constantly keeps a copy of the status of loT devices, so that they can analyze attacks before they affect physical infrastructure. With federated learning, multiple loT gateways can work together to train security models without exposing sensitive data, thus keeping security models private. Validated threat signatures and attack intelligence are kept in an immutable format in a blockchain-based security ledger to be shared securely amongst network participants. If suspicious activity is detected, the system automatically triggers preventive measures like device isolation, dynamic access control changes, traffic filtering arid self-healing network reconfiguration. The invention is useful in the field of smart home, healthcare systems, industrial automation, smart cities, transportation networks, and critical infrastructure protection. The proposed architecti.rre offers considerable gains in accuracy of detection, fewer false positives, and faster response time to attack, while additionally providing increased resilience to new cyber threats in the resource-constrained loT environments .

Disclaimer: Curated by HT Syndication.