Published July 30, 2023 | Version CC BY-NC-ND 4.0
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Proposing A New Approach for Detecting Malware Based on the Event Analysis Technique

Creators

  • 1. Posts and Telecommunications Institute of Technology;
  • 2. Faculty of Information Technology, Hanoi University.

Contributors

Contact person:

  • 1. Posts and Telecommunications Institute of Technology;

Description

Abstract: The attack technique by the malware distribution form is a dangerous, difficult to detect and prevent attack method. Current malware detection studies and proposals are often based on two main methods: using sign sets and analyzing abnormal behaviors using machine learning or deep learning techniques. This paper will propose a method to detect malware on Endpoints based on Event IDs using deep learning. Event IDs are behaviors of malware tracked and collected on Endpoints' operating system kernel. The malware detection proposal based on Event IDs is a new research approach that has not been studied and proposed much. To achieve this purpose, this paper proposes to combine different data mining methods and deep learning algorithms. The data mining process is presented in detail in section 2 of the paper.

Notes

Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved.

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Journal article: 2278-3075 (ISSN)

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Subjects

ISSN: 2278-3075 (Online)
https://portal.issn.org/resource/ISSN/2278-3075#
Retrieval Number: 100.1/ijitee.H96510712823
https://www.ijitee.org/portfolio-item/H96510712823/
Journal Website: www.ijitee.org
https://www.ijitee.org/
Publisher: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)
https://www.blueeyesintelligence.org/