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International Conference on Network and System Security

NSS 2020: Network and System Security pp 388–407Cite as

ESCAPADE: Encryption-Type-Ransomware: System Call Based Pattern Detection

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12570))

Abstract

Encryption-type ransomware has risen in prominence lately as the go-to malware for threat actors aiming to compromise Android devices. In this paper, we present a ransomware detection technique based on behaviours observed in the system calls performed by the malware. We identify and present some common high-level system call behavioural patterns targeted at encryption-type ransomware and evaluate these patterns. We further present our repeatable and extensible methodology for extracting the system call log and patterns.

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Notes

  1. 1.

    https://crow.org.nz/tools/ransomwaresystemcalldataset.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Waikato, Hamilton, New Zealand

    Christopher Jun-Wen Chew & Vimal Kumar

  2. Department of Software Engineering, University of Waikato, Hamilton, New Zealand

    Panos Patros & Robi Malik

Authors
  1. Christopher Jun-Wen Chew
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  2. Vimal Kumar
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  3. Panos Patros
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  4. Robi Malik
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Corresponding author

Correspondence to Vimal Kumar .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wroclaw, Poland

    Mirosław Kutyłowski

  2. Swinburne University of Technology, Hawthorn, VIC, Australia

    Jun Zhang

  3. James Cook University, Douglas, QLD, Australia

    Chao Chen

Appendix

Appendix

figure a
figure b
Table 2. List of token names and their respective pattern
Full size table
Table 3. List of common behavioural patterns discovered and their token representation
Full size table

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Chew, C.JW., Kumar, V., Patros, P., Malik, R. (2020). ESCAPADE: Encryption-Type-Ransomware: System Call Based Pattern Detection. In: Kutyłowski, M., Zhang, J., Chen, C. (eds) Network and System Security. NSS 2020. Lecture Notes in Computer Science(), vol 12570. Springer, Cham. https://doi.org/10.1007/978-3-030-65745-1_23

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  • DOI: https://doi.org/10.1007/978-3-030-65745-1_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65744-4

  • Online ISBN: 978-3-030-65745-1

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