A Ransomware Classification Framework Based on File-Deletion and File-Encryption Attack Structures
Aaron Zimba, Mumbi Chishimba, Sipiwe Chihana

TL;DR
This paper introduces a classification framework for ransomware based on attack structures, helping to understand their severity and potential for data recovery, which can inform better mitigation strategies.
Contribution
It proposes a novel ransomware categorization framework based on attack structures, aiding in assessing severity and recovery potential.
Findings
Many ransomware exhibit flaws allowing data recovery without paying
Higher severity categories (CAT4, CAT5) are better mitigated by encryption
Lower categories (CAT1, CAT2) are easily mitigated without decryption
Abstract
Ransomware has emerged as an infamous malware that has not escaped a lot of myths and inaccuracies from media hype. Victims are not sure whether or not to pay a ransom demand without fully understanding the lurking consequences. In this paper, we present a ransomware classification framework based on file-deletion and file-encryption attack structures that provides a deeper comprehension of potential flaws and inadequacies exhibited in ransomware. We formulate a threat and attack model representative of a typical ransomware attack process from which we derive the ransomware categorization framework based on a proposed classification algorithm. The framework classifies the virulence of a ransomware attack to entail the overall effectiveness of potential ways of recovering the attacked data without paying the ransom demand as well as the technical prowess of the underlying attack…
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Taxonomy
TopicsAdvanced Malware Detection Techniques · Digital and Cyber Forensics · Network Security and Intrusion Detection
