An Analysis Of System Calls Using J48 And JRip For Malware Detection

• Main Authors: Abdollah, Mohd Faizal, Abdullah, Raihana Syahirah, S.M.M Yassin, S.M. Warusia Mohamed, Selamat, Siti Rahayu, Mohd Saudi, Nur Hidayah
• Format: Article
• Language: English
• Published: Little Lion Scientific Islamabad Pakistan 2018
• Online Access: http://eprints.utem.edu.my/id/eprint/25307/2/28VOL96NO13.PDF; http://eprints.utem.edu.my/id/eprint/25307/; http://www.jatit.org/volumes/Vol96No13/28Vol96No13.pdf

The evolution of malware possesses serious threat ever since the concept of malware took root in the technology industry. The malicious software which is specifically designed to disrupt, damage, or gain authorized access to a computer system has made a lot of researchers try to develop a new and better technique to detect malware but it is still inaccurate in distinguishing the malware activities and ineffective. To solve the problem, this paper proposed the integrated machine learning methods consist of J48 and JRip in detecting the malware accurately. The integrated classifier algorithm applied to examine, classify and generate rules of the pattern and program behaviour of system call information. The outcome then revealed the integrated classifier of J48 and JRip outperforming the other classifier with 100% detection of attack rate