首页|Research on Machine Learning Detailed by a Researcher at COMSATS University Isla mabad (Implementation of Lightweight Machine Learning-Based Intrusion Detection System on IoT Devices of Smart Homes)
Research on Machine Learning Detailed by a Researcher at COMSATS University Isla mabad (Implementation of Lightweight Machine Learning-Based Intrusion Detection System on IoT Devices of Smart Homes)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in artific ial intelligence. According to news reporting from Punjab, Pakistan, by NewsRx j ournalists, research stated, "Smart home devices, also known as IoT devices, pro vide significant convenience; however, they also present opportunities for attac kers to jeopardize homeowners' security and privacy." Funders for this research include Department of Cyber Security And Networks, Sch ool of Computing, Engineering And Built Environment, Glasgow Caledonian Universi ty, Uk. Our news correspondents obtained a quote from the research from COMSATS Universi ty Islamabad: "Securing these IoT devices is a formidable challenge because of t heir limited computational resources. Machine learning-based intrusion detection systems (IDSs) have been implemented on the edge and the cloud; however, IDSs h ave not been embedded in IoT devices. To address this, we propose a novel machin e learning-based two-layered IDS for smart home IoT devices, enhancing accuracy and computational efficiency. The first layer of the proposed IDS is deployed on a microcontroller-based smart thermostat, which uploads the data to a website h osted on a cloud server. The second layer of the IDS is deployed on the cloud si de for classification of attacks. The proposed IDS can detect the threats with a n accuracy of 99.50% at cloud level (multiclassification)."
COMSATS University IslamabadPunjabPa kistanCybersecurityCyborgsEmerging TechnologiesMachine Learning
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