Faculty of Computer and Information Researchers Yield New Study Findings on Mach ine Learning (Enhanced an Intrusion Detection System for IoT networks through ma chine learning techniques: an examination utilizing the AWID dataset)
Faculty of Computer and Information Researchers Yield New Study Findings on Mach ine Learning (Enhanced an Intrusion Detection System for IoT networks through ma chine learning techniques: an examination utilizing the AWID dataset)
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New study results on artificial intell igence have been published. According to newsreporting from the Faculty of Comp uter and Information by NewsRx journalists, research stated, “Therapid expansio n of Internet of Things (IoT) technologies has revolutionized connectivity but h as alsoexposed users to increased cyber threats. This study aims to enhance Int rusion Detection Systems (IDSs)for IoT networks by employing advanced machine l earning (ML) techniques and addressing the challengeof dataset selection, movin g beyond outdated standards such as KDD99 and NSL-KDD99.”
Key words
Faculty of Computer and Information/Cyb ersecurity/Cyborgs/Emerging Technologies/Machine Learning
NETL
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