Intellectual Property India Publishes Patent Application for 'AI-Powered Security Monitoring And Threat Detection System With Quantum-Resistant Analytics And Federated Learning For Adaptive Cybersecurity' Filed by Apexcognita Private Limited

MUMBAI, India, April 10 -- Intellectual Property India has published a patent application (202441075314 A) filed by Apexcognita Private Limited, Hyderabad, Telangana, on Oct. 4, 2024, for 'ai-powered security monitoring and threat detection system with quantum-resistant analytics and federated learning for adaptive cybersecurity.'

Inventor(s) include Babu Siva Prasad Dachepalli.

The application for the patent was published on April 10, under issue no. 15/2026.

According to the abstract released by the Intellectual Property India: "The AI-Powered Security Monitoring and Threat Detection (AISMTD) system (100) is an advanced cybersecurity solution that integrates quantum-resistant cryptography, artificial intelligence, and federated learning to provide real-time, adaptive threat detection and response. The system employs a multi-layer data ingestion framework (102), AI-driven anomaly detection (104), quantum-resistant cryptographic analysis (106), and predictive threat modelling (110). Its federated learning network (112) enables privacy-preserving threat intelligence sharing across organizations, while the quantum-safe secure enclave (114) protects sensitive AI models and data. The AISMTD system is designed to evolve with the threat landscape, offering a future-proof solution for diverse digital ecosystems including cloud, edge, and IoT environments. This invention addresses the urgent need for adaptive, AI-driven security systems that can withstand future quantum computing attacks while providing comprehensive protection against evolving cyber threats. 12. DESCRIPTION OF THE DRAWINGS Fig. 1: Overall System Architecture of AISMTD Fig. 2: Multi-Layer Data Ingestion Framework Fig. 3: AI-Driven Anomaly Detection Engine Fig. 4: Quantum-Resistant Cryptographic Analysis Module Fig. 5: Predictive Threat Modeling System Fig. 6: Automated Threat Response Orchestrator Fig. 7: Federated Learning Network for Threat Intelligence Sharing Fig. 8: Quantum-Safe Secure Enclave for AI Model Protection Fig. 9: Adaptive Security Posture Management Fig. 10: Edge Computing Security Module Architecture Fig. 11: Quantum Resilience Strategy Implementation Fig. 12: AI Model Architecture for Threat Detection and Response Fig. 13: Federated Learning for Collaborative Threat Intelligence Fig. 14: Explainable AI for Security Decision Justification Fig. 15: Scalability Scenarios Comparison 13. DRAWINGS (Refer to separate sheets for detailed diagrams)."

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