eprintid: 3998
rev_number: 6
eprint_status: archive
userid: 274
dir: disk0/00/00/39/98
datestamp: 2020-07-10 05:51:47
lastmod: 2020-07-10 05:51:47
status_changed: 2020-07-10 05:51:47
type: article
succeeds: 3997
metadata_visibility: show
creators_name: Tran, Nghi Phu
creators_name: Nguyen, Dai Tho
creators_name: Le, Huy Hoang
creators_name: Nguyen, Ngoc Toan
creators_name: Nguyen, Ngoc Binh
creators_id: tnphvan@gmail.com
creators_id: nguyendaitho@vnu.edu.vn
creators_id: hoangle.hvan@gmail.com
creators_id: ngoctoan.hvan@gmail.com
creators_id: nn_binh@kcg.edu
corp_creators: People's Security Academy
corp_creators: VNU University of Engineering and Technology
corp_creators: The Kyoto College of Graduate Studies for Informatics
title: An Efficient Algorithm to Extract Control Flow-based Features for IoT Malware Detection
ispublished: inpress
subjects: IT
subjects: isi
divisions: avitech
divisions: fac_fit
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%.
date: 2020
publisher: Oxford University Press
official_url: https://academic.oup.com/comjnl
full_text_status: public
publication: The Computer Journal
refereed: TRUE
issn: 0010-4620
citation:   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)  
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3998/1/CJ.pdf