Robotics & Machine Learning Daily News2024,Issue(Sep.9) :74-75.

Faculty of Applied Sciences Researchers Discuss Research in Machine Learning (Ad vanced Machine Learning Based Malware Detection Systems)

Robotics & Machine Learning Daily News2024,Issue(Sep.9) :74-75.

Faculty of Applied Sciences Researchers Discuss Research in Machine Learning (Ad vanced Machine Learning Based Malware Detection Systems)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial in telligence have been published. According to news originating from Macau, People ’s Republic of China, by NewsRx editors, the research stated, “In the area of ma chine learning (ML) training data optimization through the construction of compa ct data, the focus of this paper is presented.” Funders for this research include Macao Polytechnic University. Our news journalists obtained a quote from the research from Faculty of Applied Sciences: “The concept of compact data design, aimed at creating an optimized da taset that maximizes benefits without the need to manage a vast amount of comple x data, is introduced. Improvements in the methods for optimizing ML training ha ve been incorporated into the development of artificial intelligence (AI) system s. The introduction of understanding ML training datasets as a facet of Explaina ble AI (XAI), comprehensible to humans, has been made. Among the methods of XAI, the evaluation of input feature importance stands out as a way to enhance the a ccuracy of complex ML models. The innovative method of compact data design for o ptimizing ML training through dataset reduction is proposed. The performance of an ML-based malware detection system, along with its variant utilizing compact d ata, has been assessed, demonstrating the maintenance of 99% accur acy.”

Key words

Faculty of Applied Sciences/Macau/Peop le’s Republic of China/Cybersecurity/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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