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2015
ACM

Detecting Clusters of Fake Accounts in Online Social Networks

3 years 3 months ago
Detecting Clusters of Fake Accounts in Online Social Networks
Fake accounts are a preferred means for malicious users of online social networks to send spam, commit fraud, or otherwise abuse the system. A single malicious actor may create dozens to thousands of fake accounts in order to scale their operation to reach the maximum number of legitimate members. Detecting and taking action on these accounts as quickly as possible is imperative in order to protect legitimate members and maintain the trustworthiness of the network. However, any individual fake account may appear to be legitimate on first inspection, for example by having a real-sounding name or a believable profile. In this work we describe a scalable approach to finding groups of fake accounts registered by the same actor. The main technique is a supervised machine learning pipeline for classifying an entire cluster of accounts as malicious or legitimate. The key features used in the model are statistics on fields of user-generated text such as name, email address, company or uni...
Cao Xiao, David Mandell Freeman, Theodore Hwa
Added 17 Apr 2016
Updated 17 Apr 2016
Type Journal
Year 2015
Where CCS
Authors Cao Xiao, David Mandell Freeman, Theodore Hwa
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