The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2021.0120355
PDF

Detecting Malware based on Analyzing Abnormal behaviors of PE File

Author 1: Lai Van Duong
Author 2: Cho Do Xuan

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 3, 2021.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Attack by spreading malware is a dangerous attack form that is very difficult to detect and prevent. Attack techniques that spread malware through users and then escalate privileges in the system are increasingly used by attackers. The three main methods and techniques for tracking and detecting malware that is being currently studied and applied include signature-based, behavior-based, and hybrid techniques. In particular, the behavior-based technique with the support of machine learning algorithms has given high efficiency. On the other hand, in reality, attackers often find various ways and techniques to hide behaviors of the malware based on the Portable Executable File Format (PE File) of the malware. This makes it difficult for surveillance systems to detect malware. From the above reasons, in this paper, we propose a malware detection method based on the PE File analysis technique using machine learning and deep learning algorithms. Our main contribution in this paper is proposing some features that represent abnormal behaviors of malware based on PE File and the efficiency of some machine learning algorithms in the classification process.

Keywords: Malware; portable executable file format; detection malware; abnormal behaviors; machine learning; deep learning

Lai Van Duong and Cho Do Xuan, “Detecting Malware based on Analyzing Abnormal behaviors of PE File” International Journal of Advanced Computer Science and Applications(IJACSA), 12(3), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120355

@article{Duong2021,
title = {Detecting Malware based on Analyzing Abnormal behaviors of PE File},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120355},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120355},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {3},
author = {Lai Van Duong and Cho Do Xuan}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org