Behaviour Based Ransomware Detection
Author(s) -
Christopher Jun Wen Chew,
Vimal Kumar
Publication year - 2019
Publication title -
epic series in computing
Language(s) - English
Resource type - Conference proceedings
ISSN - 2398-7340
DOI - 10.29007/t5q7
Subject(s) - ransomware , malware , computer science , computer security , signature (topology) , mobile malware , mathematics , geometry
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.
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