An Efficient Algorithm to Extract Control Flow-based Features for IoT Malware Detection

Tran, Nghi Phu and Nguyen, Dai Tho and Le, Huy Hoang and Nguyen, Ngoc Toan and Nguyen, Ngoc Binh (2020) An Efficient Algorithm to Extract Control Flow-based Features for IoT Malware Detection. The Computer Journal . ISSN 0010-4620 (In Press)

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Abstract

Control flow-based feature extraction method has the ability to detect malicious code with higher accuracy than traditional text-based methods. Unfortunately, this method has been encountering with the NP-hard problem, which is infeasible for the large-sized and high-complexity programs. To tackle this, we propose a control flow-based features extraction dynamic programming algorithm (CFD) for fast extraction of control flow-based features with polynomial time O(N^2), where N is the number of basic blocks in decompiled executable codes. From the experimental results, it is demonstrated that the proposed algorithm is more efficient and effective in detecting malware than the existing ones. Applying our algorithm to an IoT dataset gives better results on 3 measures: Accuracy (AC) = 99.05%, False Positive Rate (FPR) = 1.31% and False Negative Rate (FNR) = 0.66%.

Item Type:	Article
Subjects:	Information Technology (IT) ISI-indexed journals
Divisions:	Advanced Insitute of Engineering and Technology (AVITECH) Faculty of Information Technology (FIT)
Depositing User:	Dr. Dai Tho Nguyen
Date Deposited:	10 Jul 2020 05:51
Last Modified:	10 Jul 2020 05:51
URI:	http://eprints.uet.vnu.edu.vn/eprints/id/eprint/3998

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