Differential Area Analysis for Ransomware: Attacks, Countermeasures, and LimitationsShow others and affiliations
2025 (English)In: IEEE Transactions on Dependable and Secure Computing, ISSN 1545-5971, E-ISSN 1941-0018, Vol. 22, no 4, p. 3449-3464Article in journal (Refereed) Published
Abstract [en]
Crypto-ransomware attacks have been a growing threat over the last few years. The goal of every ransomware strain is encrypting user data, such that attackers can later demand users a ransom for unlocking their data. To maximise their earning chances, attackers equip their ransomware with strong encryption which produce files with high entropy values. Davies et al. proposed Differential Area Analysis (DAA), a technique that analyses files headers to differentiate compressed, regularly encrypted, and ransomware-encrypted files. In this paper, first we propose three different attacks to perform malicious header manipulation and bypass DAA detection. Then, we propose three countermeasures, namely 2-Fragments (2F), 3-Fragments (3F), and 4-Fragments (4F), which can be applied equally against each of the three attacks we propose. We conduct a number of experiments to analyse the ability of our countermeasures to detect ransomware-encrypted files, whether implementing our proposed attacks or not. Last, we test the robustness of our own countermeasures by analysing the performance, in terms of files per second analysed and resilience to extensive injection of low-entropy data. Our results show that our detection countermeasures are viable and deployable alternatives to DAA.
Place, publisher, year, edition, pages
IEEE, 2025. Vol. 22, no 4, p. 3449-3464
Keywords [en]
Ransomware detection, entropy, differential area analysis, vulnerabilities, invasive software
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-121212DOI: 10.1109/tdsc.2025.3532324ISI: 001561098500015Scopus ID: 2-s2.0-85216116780OAI: oai:DiVA.org:oru-121212DiVA, id: diva2:1960095
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)2025-05-222025-05-222025-12-05Bibliographically approved