MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641077779 A) filed by Thamaraimanian Mk; and Dr. P. Balamurugan on June 24, 2026, for Exploring Context- Aware Zero Trust Approaches With Explainable Ai For Data Driven Security.
Inventors include Thamaraimanian Mk; and Dr. P. Balamurugan.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: Abstract This invention discloses a Context-Aware Zero Trust (CAZT) model integrated with Explainable Artificial Intelligence (XAI) that addresses the limitations of traditional perimeter-based security architectures. As digital infrastructures evolve and cyberattacks grow more sophisticated and distributed, the Zero Trust Architecture (ZTA) paradigm.founded on the principle of "Never Trust, Always Verify".has emerged as a crucial security framework. However, existing ZTA implementations lack contextual awareness and transparency in decision-making. The proposed CAZT model overcomes these deficiencies through a dual-layer trust assessment system comprising: (i) Critical Trust (CT), which evaluates baseline security compliance via cloud microservice parameters including Authentication, Authorization, Encryption, and Logging; and (ii) Bond Trust (BT), which assesses contextual relationships among users, devices, and data through semantic and syntactic analysis employing Word2vec embeddings, cosine similarity, and BLEU scoring. A hierarchical Decision Engine (DE) dynamically grants, denies, or flags access requests based on computed trust scores. Experimental evaluation using a synthetic dataset of 17,625 attributes generated via Synthea demonstrated an Fl-score of 93.5% and a decision confidence score of 98.55%. significantly outperforming conventional n-gram and BLEU-based models. The framework also exhibited improved threat detection and lower false-positive rates, validating its suitability for realtime security environments.
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