RANSOMWARE DETECTION BASED ON HARDWARE SENSOR INFORMATION

NUR HIDAYAH M S; FAIZAL M A; WARUSIA YASSIN; KAMIL KUROBONOV

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RANSOMWARE DETECTION BASED ON HARDWARE SENSOR INFORMATION

Author(s)

NUR HIDAYAH M S Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Malaysia (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia

FAIZAL M A Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Malaysia (UTeM), Hang Tuah Jaya, Durian Tunggal, Melaka, Malaysia

WARUSIA YASSIN Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Malaysia (UTeM), Hang Tuah Jaya, Durian Tunggal, Melaka, Malaysia

KAMIL KUROBONOV Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Malaysia (UTeM), Hang Tuah Jaya, Durian Tunggal, Melaka, Malaysia

Abstract

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.

Publication Details

Page(s) 465-476

DOI DOI not available

Published Journal: Journal of Theoretical and Applied Information Technology, Volume: 98, Issue: 3, Year: 2020

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Keywords

machine learning, Ransomware, Malware Detection, Hardware Performance

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