To Örebro University

oru.seÖrebro University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Differential Area Analysis for Ransomware: Attacks, Countermeasures, and Limitations
Department of Mathematics, University of Padova, Padova, Italy.
Department of Mathematics, University of Padova, Padova, Italy.
Department of Mathematics, University of Padova, Padova, Italy.
Department of Mathematics, University of Padova, Padova, Italy.ORCID iD: 0000-0002-3612-1934
Show others and affiliations
2025 (English)In: IEEE Transactions on Dependable and Secure Computing, ISSN 1545-5971, E-ISSN 1941-0018, p. 1-16Article in journal (Refereed) Epub ahead of print
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. p. 1-16
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-121212DOI: 10.1109/tdsc.2025.3532324Scopus ID: 2-s2.0-85216116780OAI: oai:DiVA.org:oru-121212DiVA, id: diva2:1960095
Available from: 2025-05-22 Created: 2025-05-22 Last updated: 2025-05-22Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Giaretta, Alberto

Search in DiVA

By author/editor
Conti, MauroGiaretta, Alberto
By organisation
School of Science and Technology
In the same journal
IEEE Transactions on Dependable and Secure Computing
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 9 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf