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@article{ART003029454},
author={Lee, Hyung Woo and Sangwon Na},
title={Design and Implementation of a ML-based Detection System for Malicious Script Hidden Corrupted Digital Files},
journal={Journal of Internet of Things and Convergence},
issn={2466-0078},
year={2023},
volume={9},
number={6},
pages={1-9},
doi={10.20465/KIOTS.2023.9.6.001}

TY - JOUR
AU - Lee, Hyung Woo
AU - Sangwon Na
TI - Design and Implementation of a ML-based Detection System for Malicious Script Hidden Corrupted Digital Files
JO - Journal of Internet of Things and Convergence
PY - 2023
VL - 9
IS - 6
PB - The Korea Internet of Things Society
SP - 1
EP - 9
SN - 2466-0078
AB - Malware files containing concealed malicious scripts have recently been identified within MS Office documents frequently. In response, this paper describes the design and implementation of a system that automatically detects malicious digital files using machine learning techniques. The system is proficient in identifying malicious scripts within MS Office files that exploit the OLE VBA macro functionality, detecting malicious scripts embedded within the CDH/LFH/ECDR internal field values through OOXML structure analysis, and recognizing abnormal CDH/LFH information introduced within the OOXML structure, which is not conventionally referenced. Furthermore, this paper presents a mechanism for utilizing the VirusTotal malicious script detection feature to autonomously determine instances of malicious tampering within MS Office files. This leads to the design and implementation of a machine learning-based integrated software. Experimental results confirm the software's capacity to autonomously assess MS Office file’s integrity and provide enhanced detection performance for arbitrary MS Office files when employing the optimal machine learning model.
KW - MS Office File;Malicious Script;Machine Learning;Auto-Detection System;SW Implementation.
DO - 10.20465/KIOTS.2023.9.6.001
ER -

Lee, Hyung Woo and Sangwon Na. (2023). Design and Implementation of a ML-based Detection System for Malicious Script Hidden Corrupted Digital Files. Journal of Internet of Things and Convergence, 9(6), 1-9.

Lee, Hyung Woo and Sangwon Na. 2023, "Design and Implementation of a ML-based Detection System for Malicious Script Hidden Corrupted Digital Files", Journal of Internet of Things and Convergence, vol.9, no.6 pp.1-9. Available from: doi:10.20465/KIOTS.2023.9.6.001

Lee, Hyung Woo, Sangwon Na "Design and Implementation of a ML-based Detection System for Malicious Script Hidden Corrupted Digital Files" Journal of Internet of Things and Convergence 9.6 pp.1-9 (2023) : 1.

Lee, Hyung Woo, Sangwon Na. Design and Implementation of a ML-based Detection System for Malicious Script Hidden Corrupted Digital Files. 2023; 9(6), 1-9. Available from: doi:10.20465/KIOTS.2023.9.6.001

Lee, Hyung Woo and Sangwon Na. "Design and Implementation of a ML-based Detection System for Malicious Script Hidden Corrupted Digital Files" Journal of Internet of Things and Convergence 9, no.6 (2023) : 1-9.doi: 10.20465/KIOTS.2023.9.6.001

Lee, Hyung Woo; Sangwon Na. Design and Implementation of a ML-based Detection System for Malicious Script Hidden Corrupted Digital Files. Journal of Internet of Things and Convergence, 9(6), 1-9. doi: 10.20465/KIOTS.2023.9.6.001

Lee, Hyung Woo; Sangwon Na. Design and Implementation of a ML-based Detection System for Malicious Script Hidden Corrupted Digital Files. Journal of Internet of Things and Convergence. 2023; 9(6) 1-9. doi: 10.20465/KIOTS.2023.9.6.001

Lee, Hyung Woo, Sangwon Na. Design and Implementation of a ML-based Detection System for Malicious Script Hidden Corrupted Digital Files. 2023; 9(6), 1-9. Available from: doi:10.20465/KIOTS.2023.9.6.001

Lee, Hyung Woo and Sangwon Na. "Design and Implementation of a ML-based Detection System for Malicious Script Hidden Corrupted Digital Files" Journal of Internet of Things and Convergence 9, no.6 (2023) : 1-9.doi: 10.20465/KIOTS.2023.9.6.001