MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202621028129 A) filed by Rabindranath Tagore University, Raisen, Madhya Pradesh, on March 10, for 'a system and a method to detect, predict, and mitigate network intrusions using swarm-intelligence driven adaptive thresholds, federated threat learning, and trust-validated security framework.'
Inventor(s) include Saurabh Srivastava; Dr. Jitendra Singh Kushwah; Dr. Pritaj Yadav; Dr. Sanjeev Kumar Gupta; and Dr. Rakesh Kumar.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "The present disclosure relates to a system and method for detecting, predicting, and mitigating network intrusions within a distributed communication framework, employing adaptive swarm intelligence, federated threat learning, neuromorphic behavioral prediction, and trust-validated security mechanisms. The system has a processor, memory, a real-time multi-layer data acquisition module that collects network traffic data, and a swarm intelligence optimization module that changes the thresholds for detecting intrusions based on how the network is behaving in real time. A federated threat learning module lets different nodes work together to train a model without sharing data. A neuromorphic behavioral prediction engine looks at patterns in time-based networks to guess when an intrusion might happen. A blockchain trust validation module makes sure that threat intelligence can't be changed, and a quantum-resistant security module keeps communication channels safe. A self-healing defense module automatically isolates nodes that have been hacked and starts taking steps to fix the problem. The system that was revealed offers adaptive, predictive, secure, and autonomous intrusion detection, which greatly improves the ability to respond to and protect against cyberattacks."
Disclaimer: Curated by HT Syndication.
