About: We developed a crawler to collect live malware distribution network data from publicly available sources including Google Safe Browser and VirusTotal. We then generated a dynamic graph with our visualization tool and performed malware attribution analysis. We found: 1) malware distribution networks form clusters rather than a single network; 2) those cluster sizes follow the Power Law; 3) there is a correlation between cluster size and the number of malware species in the cluster; 4) there is a correlation between the number of malware species and cyber events; and finally, 5) infrastructure components such as bridges, hubs, and persistent links play significant roles in malware distribution dynamics.   Goto Sponge  NotDistinct  Permalink

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  • We developed a crawler to collect live malware distribution network data from publicly available sources including Google Safe Browser and VirusTotal. We then generated a dynamic graph with our visualization tool and performed malware attribution analysis. We found: 1) malware distribution networks form clusters rather than a single network; 2) those cluster sizes follow the Power Law; 3) there is a correlation between cluster size and the number of malware species in the cluster; 4) there is a correlation between the number of malware species and cyber events; and finally, 5) infrastructure components such as bridges, hubs, and persistent links play significant roles in malware distribution dynamics.
Subject
  • Malware
  • Collective intelligence
  • Exponentials
  • Computer programming
  • Computer security exploits
  • Computer file systems
  • Security breaches
  • Cybercrime
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