Study Findings from University of Technology Malaysia Advance Knowledge in Machi ne Learning (Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning)

Robotics & Machine Learning Daily News2024，Issue(Mar.19) ：35-36.DOI:10.1186/s40537-024-00892-y

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Study Findings from University of Technology Malaysia Advance Knowledge in Machi ne Learning (Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on artificial intelligence is now available. According to news reporting originating from the University o f Technology Malaysia by NewsRx correspondents, research stated, “In- ternet of Th ings (IoT) devices are widely used but also vulnerable to cyberattacks that can cause security issues. To protect against this, machine learning approaches have been developed for network intrusion detection in IoT.”

Key words

University of Technology Malaysia/Cyber security/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024

Robotics & Machine Learning Daily News

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