MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202621099388 A) filed by Shubhangi Subhash Gujar on August 17, 2026, for Dqslgm: Drift Aware Quantum-Enabled 8ensemble Model For Multi-Head Learning-Based Internet Of Things Network Intrusion Detection.
Inventor includes Dr. Anand Singh Rajawat.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: The broad acceptance16of the Internet of Things (IoT) has transformed diverse industries, yet the system produced major security issues, which made the network prone to cyberattacks. Besides, the various traditional approaches has been introduced for intrusion detection, however the frameworks struggled with major challenges including high computational complexity, a lack of generalizability, flexibility issues, a lack of scalability, and higher processing time, respectively. Therefore, to overcome these limitations, the research proposes the Drift Aware Quantum-enabled 1Support Vector Machine and Light Gradient Boosting Machine ensembled model based on the Multi-head Learning (DQSLGM) 1 performing effective detection of intrusions in IoT networks. In addition, the development of DQSLGM model offers more accurate, resilient, and effective defense against emerging threats 1i4n resource constrained IoT environments. Moreover, the findings of the model demonstrate a greater accuracy of 98.72%, 98.30% sensitivity, and 99.23% specificity utilizing the CIC-IDS2017 dataset in accordance with a training percentage of 90, respectively. Keywords: 1I2ntrusion Detection System, Deep Learning, Quantum Convolutional Neural Network, Internet of Things, Voting Classifier.
Disclaimer: Curated by HT Syndication.
