MUMBAI, India, Aug. 12 -- Intellectual Property India has published a patent application (202611078554 A) filed by Mr. Abhilash Narayanan on June 25, 2026, for System And Method For Autonomous Artificial Intelligence-Based Cyber Threat Detection And Self-Healing Network Remediation.
Inventor includes Mr. Abhilash Narayanan.
The application for the patent was published on August 07, 2026, under issue no. 32/2026.
Abstract: A new approach introduces technology that uses artificial intelligence to detect cyber threats on its own while automatically repairing network damage. Instead of waiting for alerts, the design acts ahead of disruptions by combining smart forecasting tools within the infrastructure itself. Because it operates continuously, risks are spotted earlier through pattern recognition, triggering instant fixes when anomalies occur. With decision-making built into the system, corrections happen in real time, reduc-ing downtime across connected devices. Rather than relying on manual responses, adjustments unfold dynamically based on live data inputs. This setup improves resil-ience especially in complex digital setups exposed to evolving attack methods. Running across many smart nodes, the setup keeps watch on massive flows of traffic details, log records, activity trends, along with how heavily systems are used. Instead of relying on fixed rules, advanced pattern-finding models - like layered networks trained to spot sequences and spatial features - scan incoming signals for faint signs of breaches, malicious software spread, login attempts without approval, or outages. Once something unusual appears, an adaptive logic core weighs possible actions in-stantly, choosing moves that cut off infected zones while shifting tasks safely else-where, modifying settings automatically, then rebuilding damaged parts using clean backups. Hidden behind this flow, a digital twin environment helps foresee weak spots before they break, nudging defenses ahead of attacks. Because it learns nonstop from real-time inputs, this smart setup adjusts fast when new risks show up - without slowing down daily operations or using too much power. Instead of relying only on fixed rules or known attack patterns, it operates inde-pendently from start to finish, gets smarter by combining multiple models, shares in-sights safely across systems, and works just as well in private data centers as it does in mixed cloud setups. Because response times drop significantly, operations stay steady even under pres-sure. Human mistakes happen less often when automated safeguards take over rou-tine decisions. Across finance, health services, power grids, and essential networks, stability improves without constant oversight. Costs tied to managing threats decline as systems handle more tasks independently. Real-world examples show how current tools can connect smoothly into broader defense setups. Adjustments fit particular needs, so one framework works differently depending on where it is used. Digital en-vironments begin sustaining themselves, adapting before disruptions grow severe Though built on familiar needs, this system marks progress in how digital defenses adapt, running smarter without needing endless monitoring. Each example given shows possible setups, yet leaves room for other forms that follow its core ideas.
Disclaimer: Curated by HT Syndication.
