Malware Detection Using Artificial Intelligence: Techniques, Research Issues and Future Directions

Artificial intelligence (AI) is an effective technology used for upgrading the security posture against a variety of security challenges and cyber-attacks that cyber security teams may use. Malware is a software which aims to access a device without the explicit permission of its owner. Forensics investigations report that many organizations have encountered unusual records, collected by their antiviral security monitoring systems. Most of their arrangements skeptically pass a large amount of diplomatic data through various unethical strategies that make malware identification tougher. However, these procedures have varied limitations that call for an unused inquiry about the track. This study explores the complex relationship between malware detection and AI [1]. This paper provides insights into performance evaluation metrics and discusses several research issues that impede the effectiveness of existing techniques. The study also provides recommendations for future research directions and is a valuable resource for researchers and practitioners working in the field of malware detection.

Authors

Publication Details

Journal
International Journal of Engineering and Advanced Technology
Published
2024-10-23
DOI
https://doi.org/10.35940/ijeat.a4531.14011024
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Malware Detection Using Artificial Intelligence: Techniques, Research Issues and Future Directions

Mohit Kumar Mishra, Khushboo Mishra, Binay Kumar Mishra, Zahra Jabeen
International Journal of Engineering and Advanced Technology
Advanced Malware Detection Techniques
article

Malware Detection Using Artificial Intelligence: Techniques, Research Issues and Future Directions

Mohit Kumar Mishra, Khushboo Mishra, Binay Kumar Mishra, Zahra Jabeen
article en

Abstract

Artificial intelligence (AI) is an effective technology used for upgrading the security posture against a variety of security challenges and cyber-attacks that cyber security teams may use. Malware is a software which aims to access a device without the explicit permission of its owner. Forensics investigations report that many organizations have encountered unusual records, collected by their antiviral security monitoring systems. Most of their arrangements skeptically pass a large amount of diplomatic data through various unethical strategies that make malware identification tougher. However, these procedures have varied limitations that call for an unused inquiry about the track. This study explores the complex relationship between malware detection and AI [1]. This paper provides insights into performance evaluation metrics and discusses several research issues that impede the effectiveness of existing techniques. The study also provides recommendations for future research directions and is a valuable resource for researchers and practitioners working in the field of malware detection.

International Journal of Engineering and Advanced TechnologyVol. 14(1)
Openalex Percentile: Top 80%
Advanced Malware Detection Techniques
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