Version 1
: Received: 12 November 2023 / Approved: 13 November 2023 / Online: 13 November 2023 (10:09:49 CET)
How to cite:
Kang, Q.; Gu, Y. A Survey on Ransomware Threats: Contrasting Static and Dynamic Analysis Methods. Preprints2023, 2023110798. https://doi.org/10.20944/preprints202311.0798.v1
Kang, Q.; Gu, Y. A Survey on Ransomware Threats: Contrasting Static and Dynamic Analysis Methods. Preprints 2023, 2023110798. https://doi.org/10.20944/preprints202311.0798.v1
Kang, Q.; Gu, Y. A Survey on Ransomware Threats: Contrasting Static and Dynamic Analysis Methods. Preprints2023, 2023110798. https://doi.org/10.20944/preprints202311.0798.v1
APA Style
Kang, Q., & Gu, Y. (2023). A Survey on Ransomware Threats: Contrasting Static and Dynamic Analysis Methods. Preprints. https://doi.org/10.20944/preprints202311.0798.v1
Chicago/Turabian Style
Kang, Q. and Yuanyuan Gu. 2023 "A Survey on Ransomware Threats: Contrasting Static and Dynamic Analysis Methods" Preprints. https://doi.org/10.20944/preprints202311.0798.v1
Abstract
The proliferation of ransomware poses a significant threat to global cybersecurity. This study presents a comprehensive review of the methodologies employed in the detection and analysis of ransomware, emphasizing the dichotomy between static and dynamic analysis approaches. It introduces the historical context and the necessity for robust cybersecurity measures, followed by an outline of the methodological framework used to evaluate existing ransomware analysis techniques. The results detail the effectiveness and limitations of various analysis strategies, identifying key features and patterns that aid in the detection and classification of ransomware threats. The study concludes by summarizing the primary achievements, including the identification of gaps in current research and proposing future research directions aimed at enhancing ransomware detection and mitigation strategies. The synthesis provided in this survey offers a consolidated view of the state-of-the-art in ransomware threat analysis and serves as a resource for cybersecurity professionals and researchers.
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
