| ELECTRONIC ENGINEERING |
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Detecting of fake accounts with hierarchical clustering |
| FANG Yong, LIU Daosheng, HUANG Cheng |
| College of Electronics and Information Engineering, Sichuan University, Chengdu 610064, China |
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Abstract Since there are many malicious users on the Internet, popular online websites sometimes have millions of registered users. The system cannot easily distinguish between fake accounts and legitimate users. Fake accounts registered by a single malicious user often have similar profiles. This paper presents a new framework to find fake accounts in large numbers of users. The framework uses username string patterns to classify the original data and then calculates the similarity as measured by the Levenshtein distance between any two elements in one category. Hierarchical clustering with a proper threshold then finds groups of fake accounts hidden in the large amount of registration data. Tests demonstrate the effectiveness of this framework which algorithm relies less on data dimensions and features than other algorithms.
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| Keywords
data security
fake accounts
machine learning
hierarchical clustering
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Issue Date: 15 June 2017
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2017,
Vol. 57
