MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641083939 A) filed by Mohan Babu University on July 08, 2026, for Enhancing Iot Security With Hybrid Feature Selection And Deep Learning For Botnet Attack Detection.
Inventors include Dr. V. Jyothsna; Ms. G. Reddy Harika; Mr. K. Reddy Praneeth; Mr. B. Vasu; and Mr. B. Subramanyam.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: The IoT has emerged as a foundational technology in smart environments such as healthcare, homes, and industry. However, the growing scale of IoT deployment has also increased the attack surface, making IoT networks vulnerable to cyber threats, particularly botnet attacks. The present invention proposes an intelligent botnet detection system (100) that enhances IoT security using a hybrid artificial intelligence approach. Initially, network traffic is collected using a data collection unit (110) and processed by a preprocessing unit (120), which performs cleaning, normalization, and encoding operations to standardize input data. A feature selection module (130) based on Ant Lion Optimization (ALO) identifies the most relevant features, improving model efficiency and reducing computational load. These features are passed into a classification module (140), where a Deep Autoencoding Gaussian Mixture Model (DAGMM) performs unsupervised anomaly detection and classification. The system supports live traffic inspection through a real-time monitoring unit (150) and issues alerts via an alert and reporting interface (160). Data confidentiality is maintained using a data privacy and encryption module (170), while continuous adaptability is achieved through a resilience module (180), which updates detection logic based on newly observed attack behaviour.
Disclaimer: Curated by HT Syndication.
