Multipurpose Malware Detection System

In rapidly changing digital world, data has become one of the cornerstones of modern life. The amount of data is increasing exponentially and is an indispensable resource for businesses. However, the fact that data has gained so much value also brings the need to protect it from unwanted threats. In this context, efforts to develop a malware detection system have begun. The main purpose of this work is to secure the data that sustains online presence. In proposed solution, the characteristics of malware are determined, and the malicious software is classified. In this direction, signature control, static (SOEMD), and dynamic analysis (X Ran) methods have been applied for malware detection. The proposed system achieved an 87.5% of success rate in static analysis and a 96% of success rate in dynamic analysis of the unknown malware variants, highlighting its potential as a reliable tool for enhancing cybersecurity. A communication module has been developed for the dynamic analysis approach, a new quarantine system has been created to disable malware on the user's computer safely, and a full scan of the selected directory has been made possible. A user-friendly interface has been developed and improved so that users can more easily analyze the results, review warnings, and take appropriate actions.

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Publication Details

Published
2024-10-26
DOI
https://doi.org/10.1109/ubmk63289.2024.10773515
Citations
1
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.35
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article

Multipurpose Malware Detection System

İbrahim Soğukpınar, Mert Gursimsir, Cem Ayar
1 citations
Advanced Malware Detection Techniques
0.35
article

Multipurpose Malware Detection System

İbrahim Soğukpınar, Mert Gursimsir, Cem Ayar
article en
1 citations

Abstract

In rapidly changing digital world, data has become one of the cornerstones of modern life. The amount of data is increasing exponentially and is an indispensable resource for businesses. However, the fact that data has gained so much value also brings the need to protect it from unwanted threats. In this context, efforts to develop a malware detection system have begun. The main purpose of this work is to secure the data that sustains online presence. In proposed solution, the characteristics of malware are determined, and the malicious software is classified. In this direction, signature control, static (SOEMD), and dynamic analysis (X Ran) methods have been applied for malware detection. The proposed system achieved an 87.5% of success rate in static analysis and a 96% of success rate in dynamic analysis of the unknown malware variants, highlighting its potential as a reliable tool for enhancing cybersecurity. A communication module has been developed for the dynamic analysis approach, a new quarantine system has been created to disable malware on the user's computer safely, and a full scan of the selected directory has been made possible. A user-friendly interface has been developed and improved so that users can more easily analyze the results, review warnings, and take appropriate actions.

Gebze Technical University (TR)
Openalex Percentile: Top 41%
Advanced Malware Detection Techniques
0.35
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