MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541124937 A) filed by Vardhaman College Of Engineering, Ranga Reddy, Telangana, on Dec. 10, 2025, for 'deep autoencoder-based anomaly detection system for distributed databases.'
Inventor(s) include Dr. Indrajeet Sahu; Ms. Gandi Mounika Naidu; Ms. Sowmya M; Ms. Pallamoni S Madhavi; Mr. Sandiri Srinivas; and Dr. Velpuru Muni Sekhar.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "Deep Autoencoder-Based Anomaly Detection System for Distributed Databases is the proposed invention. The proposed invention is an intelligent framework designed to detect abnormal activities, data inconsistencies, and potential security threats across large-scale, multi-node database environments. The system employs deep autoencoder neural networks to learn the normal behavior of database operations by compressing and reconstructing high-dimensional operational data. Deviations between input data and its reconstruction are used to identify anomalies such as data corruption, unauthorized access, abnormal transaction patterns, or schema inconsistencies. Lightweight monitoring agents continuously collect transactional logs, query patterns, latency statistics, and replication information from distributed database nodes, which are then securely transmitted to a centralized AI engine. Detected anomalies trigger automated responses for critical issues, including blocking suspicious queries or isolating affected nodes, while non-critical events are logged for analysis."
Disclaimer: Curated by HT Syndication.
