ADVANCING TOOLS FOR SAFEGUARDING COMPUTER SYSTEMS AGAINST RANSOMWARE THREATS
Keywords:
ransomware, computer security, cyber threats, defense mechanisms, anomaly detection.Abstract
This abstract discusses modern methods and tools designed to protect computer systems from ransomware attacks. It emphasizes the need for continuous development of such tools in response to the evolution of threats and attack techniques. Various approaches are discussed, including network defense mechanisms, anomaly detection algorithms, and the utilization of artificial intelligence and machine learning. Current trends in tool development are analyzed, and recommendations for future research and practical applications are proposed.
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Cleary, G.; Cox, O.; Lau, H.; Nahorney, B.; Gorman, B.; O’Brien, D.; Wallace, S.; Wood, P.; Wueest, C. ISTR 2018. Internet Secur. Threat Rep.Symantec 2018, 23, 80–89.
Azmoodeh, A.; Dehghantanha, A.; Conti, M.; Choo, K.K.R. Detecting Crypto-ransomware in IoT Networks based on Energy Consumption Footprint. J. Ambient Intell. Hum. Comput. 2017, 9, 1141–1152.
2018.
Eset, E. ESET Security 2018; Technical Report; ESET: Bratislava, Slovakia, O’Brien, D. Ransomware 2017, An ISTR Special Report. Symantec. Available online: https://www.symantec.com/content/dam/symantec/docs/securitycenter/white-papers/istr-ransomware-2017-en.pdf (accessed on 5 April 2019).
Kumar, M.S.; Ben-Othman, J.; Srinivasagan, K. An Investigation on Wannacry Ransomware and its Detection. In Proceedings of the 2018 IEEE Symposium on Computers and Communications (ISCC), Natal, Brazil, 25–28 June 2018; pp. 1–6.
Sgandurra, D.; Muñoz-González, L.; Mohsen, R.; Lupu, E.C. Automated Dynamic Analysis of Ransomware: Benefits, Limitations and Use for Detection. arXiv 2016, arXiv:1609.03020.
Monika; Zavarsky, P.; Lindskog, D. Experimental Analysis of Ransomware on Windows and Android Platforms: Evolution and Caracterization. Procedia Comput. Sci. 2016, 94, 465–472.
Bajpai, P.; Sood, A.K.; Enbody, R. A Key-management-based Taxonomy for Ransomware. In Proceedings of the 2018 APWG Symposium on Electronic Crime Research (eCrime), San Diego, CA, USA, 15–17 May 2018; pp. 1–12.
Kelley, D. Cybesecurity in the Cognitive Era: Priming your Digital Immune System; Technical Report; IBM: Somers, NY, USA, 2016.
Endsley, M.R. Design and Evaluation for Situation Awareness Enhancement. Proc. Hum. Factors Soc. Annu. Meet. 1988, 32, 97–101.
Conti, M.; Gangwal, A.; Ruj, S. On the Economic Significance of Ransomware Campaigns: A Bitcoin Transactions Perspective. Comput.
Secur. 2018.
Hernandez-Castro, J.; Cartwright, E.; Stepanova, A. Economic Analysis of Ransomware. arXiv 2017, arXiv:1703.06660.
Gangwar, K.; Mohanty, S.; Mohapatra, A. Analysis and Detection of Ransomware Through Its Delivery Methods. In Proceedings of the International Conference on Recent Developments in Science, Engineering and Technology, Gurgaon, India, 13–14 October 2017; Springer: Berlin/Heidelberg, Germany, 2017; pp. 353–362.
Moore, C. Detecting Ransomware with Honeypot Techniques. In Proceedings of the 2016 Cybersecurity and Cyberforensics Conference (CCC), Amman, Jordan, 2–4 August 2016; pp. 77–81.
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