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      Behaviour based ransomware detection

      Chew, Christopher J.W.; Kumar, Vimal
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      Behaviour_Based_Ransomware_Detection.pdf
      Published version, 284.0Kb
      DOI
       10.29007/t5q7
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      Chew, C. J. W., & Kumar, V. (2019). Behaviour based ransomware detection. In G. Lee & Y. Jin (Eds.), Proceedings of 34th International Conference on Computers and Their Applications (CATA 2019) (Vol. 58, pp. 127–136). EasyChair. https://doi.org/10.29007/t5q7
      Permanent Research Commons link: https://hdl.handle.net/10289/12975
      Abstract
      Ransomware is an ever-increasing threat in the world of cyber security targeting vulnerable users and companies, but what is lacking is an easier way to group, and devise practical and easy solutions which every day users can utilise.

      In this paper we look at the different characteristics of ransomware, and present preventative techniques to tackle these ransomware attacks. More specifically our techniques are based on ransomware behaviour as opposed to the signature based detection used by most anti-malware software. We further discuss the implementation of these techniques and their effectiveness. We have tested the techniques on four prominent ransomware strains, WannaCry, TeslaCrypt, Cerber and Petya. In this paper we discuss how our techniques dealt with these ransomware strains and the performance impact of these techniques.
      Date
      2019
      Type
      Conference Contribution
      Publisher
      EasyChair
      Rights
      ©2019 Copyright with the authors.
      Collections
      • Computing and Mathematical Sciences Papers [1454]
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