Conference paper Open Access

Malware vs Anti-Malware Battle - Gotta Evade 'em All!

Chaffey, E.; Sgandurra, D.

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  <identifier identifierType="DOI">10.5281/zenodo.4277105</identifier>
      <creatorName>Chaffey, E.</creatorName>
      <affiliation>University of London</affiliation>
      <creatorName>Sgandurra, D.</creatorName>
      <affiliation>University of London</affiliation>
    <title>Malware vs Anti-Malware Battle - Gotta Evade 'em All!</title>
    <date dateType="Issued">2020-08-29</date>
  <resourceType resourceTypeGeneral="ConferencePaper"/>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4277104</relatedIdentifier>
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    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;The landscape of malware development is ever-changing, creating a constant catch-up contest between the defenders and the adversaries. One of the methodologies that has the potential to pose a significant threat to systems is malware evasion. This is where malware tries to determine whether it is run in a controlled environment, such as a sandbox. Similarly, a malware can also learn how an Anti-Malware System (AMS) decides whether an input program is a malware or in fact benign with the goal of bypassing it. On the other hand, the AMS tries to detect whether a malware sample is performing such evasive checks, e.g. by evaluating the results of Reverse-Turing Test (RTT). This learning process can be viewed as a &amp;lsquo;battle&amp;rsquo; between the AMS and the malware, due to the malware attempting to defeat the AMS, where a successful win for the malware would be to evade detection by the AMS and, conversely, a win for the AMS would be to correctly detect the malware and its evasive actions. We propose a visualisation-based system, called Gotta Evade &amp;lsquo;em All, that allows cyber-security analysts to clearly see the evasive and anti-evasive actions performed by the malware and the AMS during the battle.&lt;/p&gt;</description>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/100010661</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/779391/">779391</awardNumber>
      <awardTitle>Future Proofing the Connected World: A Quantum-Resistant Trusted Platform Module</awardTitle>
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