Reduction of Classifier Size and Acceleration of Classification Algorithm in Malware Detection Mechanism Using Processor Information

التفاصيل البيبلوغرافية
العنوان: Reduction of Classifier Size and Acceleration of Classification Algorithm in Malware Detection Mechanism Using Processor Information
المؤلفون: Masahiko Katoh, Kazuki Koike, Ryotaro Kobayashi
المصدر: CANDAR Workshops
بيانات النشر: IEEE, 2019.
سنة النشر: 2019
مصطلحات موضوعية: 021110 strategic, defence & security studies, Software_OPERATINGSYSTEMS, Computer science, business.industry, 0211 other engineering and technologies, Malware, 02 engineering and technology, Internet of Things, business, computer.software_genre, Algorithm, Classifier (UML), computer
الوصف: In recent years, the increase in attacks on IoT devices has become a problem, and security measures for IoT devices are urgently needed. We have proposed a malware detection mechanism using processor information and confirmed that mechanism can detect malware and its variants. In some past research, a malware detection mechanism using processor information was proposed and confirmed that the mechanism can detect malware and its variants. By offloading the proposed mechanism to hardware, we aim to realize a lightweight malware detection mechanism for IoT devices in the future. In this paper, we consider reduction of the classifier size and acceleration of the classification algorithm, which are issues in the our proposed mechanism.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::549de0b3365122bc5a517e4e19529191
https://doi.org/10.1109/candarw.2019.00066
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........549de0b3365122bc5a517e4e19529191
قاعدة البيانات: OpenAIRE