MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202641008853 A) filed by Mohan Babu University; and Dr. V. Jyothsna, Tirupati, Andhra Pradesh, on Jan. 29, for 'integrating deep learning with bio-inspired algorithms for website security.'

Inventor(s) include Dr. V. Jyothsna; Ms. Maddur Joshika; Ms. Chitipiralla Vamsipriya; Mr. M Abdul Rehman; and Mr. Gittapa Gari Abhishek.

The application for the patent was published on Feb. 13, under issue no. 07/2026.

According to the abstract released by the Intellectual Property India: "The rapid expansion of the internet has led to a significant rise in malicious web activities, including phishing, malware distribution, and spam, posing serious threats to cybersecurity. Traditional intrusion detection systems (IDS) often rely on signature-based approaches that fail to detect newly emerging or obfuscated attacks. To address these limitations, this project proposes a hybrid intrusion detection system that integrates deep learning and bio-inspired optimization algorithms for the real-time detection of malicious websites. The system employs a deep learning classifier combining Autoencoders and Long Short-Term Memory (LSTM) networks, capable of learning complex temporal and behavioral patterns in URL structures and web traffic data. To enhance model performance and reduce computational overhead, feature selection is optimized using Genetic Algorithm (GA) and Fish Swarm Optimization (FSO), both of which mimic natural evolution and swarm intelligence. The solution is trained and evaluated on the ISCX-URL2016 dataset, which contains labeled instances of phishing, malware, spam, and benign websites. The proposed system performs data preprocessing, feature optimization, classification, threat notification, and proactive security recommendation. Experimental results demonstrate high detection accuracy, reduced false positives, and strong adaptability to evolving threats. This hybrid model provides a scalable, intelligent, and adaptive cybersecurity framework that significantly improves the detection and mitigation of web-based attacks, ensuring enhanced online safety and data integrity."

Disclaimer: Curated by HT Syndication.