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Publication Detail
EvilCohort: Detecting Communities of Malicious Accounts on Online Services
Abstract
Cybercriminals misuse accounts on online services (e.g., webmails and online social networks) to perform malicious activity, such as spreading malicious content or stealing sensitive information. In this paper, we show that accounts that are accessed by botnets are a popular choice by cybercriminals. Since botnets are composed of a finite number of infected computers, we observe that cybercriminals tend to have their bots connect to multiple online accounts to perform malicious activity. We present EvilCohort, a system that detects online accounts that are accessed by a common set of infected machines. EvilCohort only needs the mapping between an online account and an IP address to operate, and can therefore detect malicious accounts on any online service (webmail services, online social networks, storage services) regardless of the type of malicious activity that these accounts perform. Unlike previous work, our system can identify malicious accounts that are controlled by botnets but do not post any malicious content (e.g., spam) on the service. We evaluated EvilCohort on multiple online services of different types (a webmail service and four online social networks), and show that it accurately identifies malicious accounts.
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Dept of Computer Science
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