MUMBAI, India, July 30 -- Intellectual Property India has published a patent application (202641082162 A) filed by Dr. D. C. Jullie Josephine; Dr. M. Parameswari; Dr. B. Yuvaraj; Dr. T. Ganesan; K. G. Saravanan; E. Munuswamy; Jasmine Margret J; T. C. Vidhya; Ramya Devi S; and S. Kumaresan on July 03, 2026, for Self-Healing Cybersecurity Architecture For Smart Critical Infrastructure.

Inventors include Dr. D. C. Jullie Josephine; Dr. M. Parameswari; Dr. B. Yuvaraj; Dr. T. Ganesan; K. G. Saravanan; E. Munuswamy; Jasmine Margret J; T. C. Vidhya; and Ramya Devi S.

The application for the patent was published on July 24, 2026, under issue no. 30/2026.

Abstract: The present invention discloses a Self-Healing Cybersecurity Architecture for Smart Critical Infrastructure that autonomously detects, analyzes, mitigates, and recovers from cyberattacks targeting critical systems such as power grids, water distribution networks, transportation networks, and industrial control systems. The proposed architecture integrates Graph Neural Network (GNN)-based anomaly detection, Deep Reinforcement Learning (DRL) using the Proximal Policy Optimization (PPO) algorithm, and Blockchain-enabled security logging to provide real-time cyber resilience and autonomous recovery. Initially, network traffic, sensor data, and operational logs are collected from distributed infrastructure nodes and transformed into graph representations, A Graph Neural Network model identifies abnonnal communication patterns and potential cyber threats by analyzing node relationships and network behavior. Upon threat detection, a Deep Reinforcement Learning agent based on the PPO algorithm dynamically determines optimal response actions, including network isolation, service migration, access restriction, and resource reallocation. Simultaneously, a blockchain-based immutable ledger records security events to ensure tamper-proof auditing and forensic analysis. The self-healing module automatically restores compromised services using containerized digital twins and redundant backup nodes, thereby minimizing system downtime and maintaining operational continuity. The architecture continuously learns from historical attack patterns and recovery outcomes, enabling adaptive defense against evolving cyber threats.

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