MUMBAI, India, Aug. 12 -- Intellectual Property India has published a patent application (202611078555 A) filed by Mr. Venkateswaran Petchiappan on June 25, 2026, for Cognitive Cyber Defense Architecture With Predictive Threat Intelligence And Automated Incident Response.
Inventor includes Mr. Venkateswaran Petchiappan.
The application for the patent was published on August 07, 2026, under issue no. 32/2026.
Abstract: The invention presented is the world’s first in presenting a cognitive cyber defense framework leveraging predictive threat intelligence with automated incident re- sponse in the development of complete adaptive dynamic self-evolving threat de-fenses for digital infrastructure environments. The current cybersecurity architecture is mostly reactive, responding with an incursion to established threat signatures upon discovery which causes most of the damage prior to the detection and initiation of mitigation procedures. The presented solution utilizes intelligent computation mod-els and machine and deep learning to predict and proactively manage emergent threats through analyses of diverse streams of network traffic data, behavioural and systemic and contextual inputs on the fly. The system is able to anticipate emergent threat by using advanced computation models that perpetually learn and adapt. The proposed solution contains several in-tegrated modules that simulate human reasoning, albeit with greater speed, scale and analytical acumen. A base layer comprises of a distributed collection network which continues to collect traffic, logging, activity patterns and externally sourced threat data in order to feed the cognitive engine where artificial deep and learning ma-chines develop a sophisticated continuously evolving understand of system activity. Subtle deviations which may provide indications of emergent threat activities, can be spotted and recognized before they become full scale penetrations and malicious acts. An innovative element is its predictive threat Intelligence module wherein all multi sourced data sets - attack data, global threat trends, individual organization risk profiles are correlated together to prognosticate possible attack methodologies with high accuracy through probabilistic models and pattern recognition. This prediction of an intrusion, possibly targeted due to geopoitical factors, recently uncovered vulnerability information and even system user activity deviations – can lead to the forecast of attack propagational routes into the digital network, and hence the enabling of proactive asset strengthening and proactive patching to proactively mitigate threat exposure. As with the prediction or incursion detection, the automated incident response sub-system is capable of initiating various response sequences without immediate or di-rect human intervention in most of the instances. It is also capable of evaluating sev-eral different options in a decision driven framework, with different possibilities ana-lyzed in parallel based on existing security policies, threat assessments and risk eval- uation parameters, to initiate a prescribed response. These can range from the identi-fication and segment isolation, to access privilege control dynamically. Forensic data collection, immediate patching, system re configuration and even con-trolled counter-operations against intruder’s can be initiated, all logged with com-prehensive audits for compliance. The inclusion of a feedback mechanism whereby the results of all predictions and responses refine, and even the modification of mod-els, to learn from past success/ failures, leads to a self-evolving system capable of addressing new and ever emergent threat actors, tactics, and methodologies. The framework also includes standard interfaces to permit seamless and flexible integra-tion with existing solutions and digital infrastructure – including for instance: busi-ness process execution systems, IoT devices and industrial control systems in hetero-geneous digital environments. Significant advantages include significant response time reduction, decreased busi-ness disruption impact, enhanced prediction accuracy (reducing the threat analyst alert overload) and scalable protection – suitable from a small business or consumer user, to large multinational enterprises. By shifting the cyber security domain from reactive defense, toward a cognitive and proactive cyber defense approach, critical security gaps with current defenses, to dy-namic, adaptive, and evolving threats like advanced persistent threats (APTs) and zero-day, will be addressed. Ultimately, the cognitive cyber defense framework will allow organizations to maintain and foster enduring digital resilience in today’s cyber-threat landscape. The architecture permits for extensibility to specific vertical requirements – be it data in the health sector, transactional security within the fi-nance sector, or industrial control systems in the critical infrastructure domain. Through integrating advanced cognitive techniques and automated operational ca-pacity, this innovative cyber-attack prevention and response solution represents the next wave in highly effective and autonomously intelligent cyber defenses.
Disclaimer: Curated by HT Syndication.
