HoneyIM: Fast Detection and Suppression of Instant Messaging Malware in Enterprise-like Networks

Mengjun Xie
College of William and Mary
USA

Zhenyu Wu
College of William and Mary
USA

Haining Wang
College of William and Mary
USA

Instant messaging (IM) has been one of most frequently-used malware attack vectors due to its popularity. Distinct from other malware, it is straightforward for IM malware to find and hit the next victim by exploiting the current victim’s contact list and playing social engineering tricks. Thus, the spread of IM malware is much harder to detect and suppress through conventional approaches. The previous solutions are ineffective to defend against IM malware in an enterprise-like network environment, mainly because of high false positive rate and the requirement of the IM server being inside the protected network. In this paper, we propose a novel IM malware detection and suppression mechanism, HoneyIM, which guarantees almost zero false positive on detecting and blocking IM malware in an enterprise-like network. The detection of HoneyIM is based on the concept of honeypot. HoneyIM uses decoy accounts to trap IM malware by exploiting malware spreading characteristics. Fed with accurate detection results, the suppression of HoneyIM can conduct a network-wide blocking. In addition, HoneyIM delivers the information about malware and infected machines to network administrators in real-time so that system quarantine or recovery can be quickly performed. The core design of HoneyIM is very generic, and can be applied to the scenarios that use either enterprise IM services or public IM services. Leveraging open-source IM client “Pidgin” and open-source client honeypot “Capture”, we build a prototype of HoneyIM and validate its efficacy through both simulations and real experiments. Our results show that HoneyIM provides effective protection against IM malware in enterprise-like networks.

Keywords: instant messaging, malware, decoy users

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