Scrutinized System Calls Information Using J48 And Jrip For Malware Behaviour Detection

Abdollah, Mohd Faizal and S. M. M Yassin, S. M. Warusia Mohamed and Mohd Saudi, Nur Hidayah (2019) Scrutinized System Calls Information Using J48 And Jrip For Malware Behaviour Detection. Journal Of Engineering Science And Technology, 14 (1). pp. 291-304. ISSN 1823-4690

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Malware is considered as one of most emerging threats due to Cybercriminals work diligently to make most of the part of the users’ network of computers as their target. A number of researchers keep on proposing the various alternative framework consisting detection methods day by days in combating activities such as single classification and the rule-based approach. However, such detection method still lacks in differentiate the malware behaviours and cause the rate of falsely identified rate, i.e., false positive and false negative increased. Therefore, integrated machine learning techniques comprise J48 and Jrip are proposed as a solution to distinguish malware behaviour more accurately. This integrated classifier algorithm applied to analyse, classify and generate rules of the pattern and program behaviour of system call information in which, the legal and illegal behaviours could identify. The result showed that the integrated classifier between J48 and Jrip significantly improved the detection rate as compared to the single classifier.

Item Type: Article
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Information and Communication Technology > Department of System and Computer Communication
Depositing User: Mohd Hannif Jamaludin
Date Deposited: 05 Mar 2020 12:13
Last Modified: 05 Mar 2020 12:13
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