Ransomware attacks have emerged as a major cybersecurity threat wherein user data is encrypted upon system infection. Latest ransomware strands using advanced obfuscation techniques along with offline C2 Server capabilities are hitting individual users and big corporations alike. This problem has caused business disruption and, of course, financial loss. Since there is no such consolidated framework that can classify, detect and mitigate ransomware attacks in one go, the authors of this review are motivated to present Detection Avoidance Mitigation (DAM), a theoretical framework to review and classify techniques, tools, and strategies to detect, avoid and mitigate ransomware. This review and the presented framework may be beneficial for cybersecurity, information governance, and legal discovery professionals seeking to deal with the challenge of ransomware.

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