Ransomware Classification and Detection: A Supervised Machine Learning Approach
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9707-7_24
Reference20 articles.
1. Chittooparambil HJ, Shanmugam B, Azam S, Kannoorpatti K, Jonkmon M, Narayanasamy G (2018) A review of ransomware families and detection methods. In: International conference of reliable information and communication technology, pp 588–597
2. Burnap P, French R, Turner F, Jones K (2018) Malware classification using self organising feature maps and machine activity data. Comput Sec 73:399–410
3. https://www.statista.com/statistics/494947/ransomware-attacks-per-year-worldwide/
4. https://dataprot.net/statistics/ransomware-statistics/
5. https://www.sangfor.com/blog/cybersecurity/ransomware-attacks-2022-overview
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