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  • 标题:RANSOMWARE DETECTION BASED ON HARDWARE SENSOR INFORMATION
  • 本地全文:下载
  • 作者:NUR HIDAYAH M. S ; FAIZAL M. A ; WARUSIA YASSIN
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2020
  • 卷号:98
  • 期号:3
  • 页码:465-476
  • 出版社:Journal of Theoretical and Applied
  • 摘要:Ransomware is a growing threat to the computer world that encrypts victim’s data and asks for ransom for decryption key which causes financial loss and severe disruption in the organization. Despite the threat and an extremely growing number of cases of ransomware infection, various countermeasures have been proposed since the first appearance of ransomware but there is still not enough information on the approaches to detect it. Thus, this paper will perform ransomware detection using the behavioral method on information retrieved from computer sensors such as CPU, Main Memory and Disk Memory. The different classification method such as Naïve Bayes, J48 and KStar algorithm will be used to detect the ransomware attack and the measured value in term of accuracy.
  • 关键词:Ransomware;Malware Detection;Hardware Performance;Classification;Machine Learning
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