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Advancements in automated malware analysis: evaluating the efficacy of open-source tools in detecting and mitigating emerging malware threats to US businesses
Department of Information Systems & Business Analytics, Hankamer School of Business, Baylor University, Waco, TX
Review
International Journal of Science and Research Archive, 2024, 12(02), 1958–1964.
Article DOI: 10.30574/ijsra.2024.12.2.1488
Publication history:
Received on 04 July 2024; revised on 13 August 2024; accepted on 15 August 2024
Abstract:
Malware, short for malicious software, represents a significant and evolving threat to computer systems, targeting individuals, corporations, and governments globally. This paper explores the multifaceted nature of malware, which includes viruses, worms, Trojans, and more, and delves into how they compromise systems by disrupting services, stealing sensitive data, and denying access. Modern malware is increasingly sophisticated, evading traditional detection methods and posing challenges to cybersecurity professionals. This review outlines key methodologies in malware analysis, including MARE (Malware Analysis Reverse Engineering) and SAMA (Systematic Approach to Malware Analysis), which offer systematic frameworks for understanding and mitigating malware threats. Additionally, the paper highlights the challenges of malware analysis, such as the complexity of advanced malware variants and the limitations of current detection techniques. By examining the types of malwares, from ransomware to keyloggers, and discussing the signs of an attack, the paper underscores the importance of ongoing research and the development of more robust analytical tools. The insights provided aim to enhance the preparedness of IT professionals in combating emerging threats, emphasizing the necessity of a comprehensive understanding of malware behavior for effective defense strategies.
Keywords:
Malware; Cybersecurity; Ransomware; Dynamic Analysis; MARE (Malware Analysis Reverse Engineering); SAMA (Systematic Approach to Malware Analysis)
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
