MUMBAI, India, Oct. 12 -- Intellectual Property India has published a patent application (202641118571 A) filed by Madhankumar C; Dr. K. Amuthambigaiyin Sundari - Rvs Institute Of Technology; Mr. S. Gunasekaran - V. S. B. Engineering College; Ms. P. Keerthika - Kings Engineering College; Mrs. K. V. Kiruthikaa - Erode Sengunthar Engineering College; Dr. S. Arunkumar - Nehru Institute Of Engineering And Technology; Mrs. V. Gomathi - Care College Of Engineering; Dr. M. Gokilavani - Dayananda Sagar University; M. S. Vinu - Jct College Of Engineering And Technology; and Ms. R. Devi - R. M. K. Engineering College on October 04, 2026, for Blockchain-Secured Generative Aiot Network For Autonomous Cyber-Physical System Protection.
Inventors include Dr. K. Amuthambigaiyin Sundari - Rvs Institute Of Technology; Mr. S. Gunasekaran - V. S. B. Engineering College; Ms. P. Keerthika - Kings Engineering College; Mrs. K. V. Kiruthikaa - Erode Sengunthar Engineering College; Dr. S. Arunkumar - Nehru Institute Of Engineering And Technology; Mrs. V. Gomathi - Care College Of Engineering; Dr. M. Gokilavani - Dayananda Sagar University; M. S. Vinu - Jct College Of Engineering And Technology; and Ms. R. Devi - R. M. K. Engineering College.
The application for the patent was published on October 09, 2026, under issue no. 41/2026.
Abstract: ABSTRACT Blockchain-Secured Generative AIoT Network for Autonomous Cyber-Physical System Protection The present invention relates to a Blockchain-Secured Generative AIoT Network for providing autonomous, real-time, and resilient protection of cyber-physical systems (CPS) against cyber threats, abnormal operational conditions, unauthorized activities, and system failures. The proposed system integrates Internet of Things (IoT) devices, Artificial Intelligence of Things (AIoT), Generative Artificial Intelligence, blockchain technology, edge computing, multi-source data fusion, behavioral analysis, and autonomous response mechanisms within a distributed security architecture. The system comprises a plurality of heterogeneous sensors and cyber-physical devices configured to acquire real-time information relating to physical processes, device states, network traffic, system commands, environmental conditions, and operational parameters. An edge intelligence layer preprocesses the acquired information and performs real-time feature extraction, anomaly detection, behavioral analysis, and threat assessment. A Generative AI engine analyzes historical and real-time information to identify previously unknown or evolving attack patterns, generate potential threat scenarios, predict abnormal system behavior, and assist in determining appropriate protective actions. A blockchain security layer provides decentralized integrity and traceability for selected sensor events, device identities, security alerts, model updates, access transactions, and response records. Distributed ledger mechanisms and smart contracts are configured to validate authorized transactions, maintain tamper-resistant security records, and enforce predefined access and operational policies without relying exclusively on a centralized security authority. The system further comprises an autonomous protection module configured to correlate AI generated threat intelligence with physical- system states and initiate authorized protective responses. The responses may include isolating a compromised device, modifying access privileges, blocking suspicious communication, adjusting operational parameters, generating security alerts, or transferring control to an authorized human operator according to predefined safety policies. A continuous feedback mechanism enables the Generative AI engine to learn from security events, system responses, and operational outcomes, thereby improving future threat detection and response. Accordingly, the invention provides a decentralized, intelligent, adaptive, tamper-resistant, and autonomous cybersecurity architecture for protecting interconnected cyber-physical systems. The integration of blockchain-secured identity and transaction management with Generative AI-based predictive and generative threat intelligence enables real-time protection while improving data integrity, auditability, resilience, and autonomous security decision making across distributed AIoT environments.
Disclaimer: Curated by HT Syndication.
