Malicious users are a threat to many sites and defending against them demands innovative countermeasures. When malicious users join sites, they provide limited information about themselves. With this limited information, sites can find it difficult to distinguish between a malicious user and a normal user. In this study, we develop a methodology that identifies malicious users with limited information. As information provided by malicious users can vary, the proposed methodology utilizes minimum information to identify malicious users. It is shown that as little as 10 bits of information can help greatly in this challenging task. The experiments results verify that this methodology is effective in identifying malicious users in the realistic scenario of limited information availability.
@inproceedings{reza2015bits,
title = {10 Bits of Surprise: Detecting Malicious Users with Minimum Information},
author = {Reza Zafarani and Huan Liu},
year = {2015},
keywords = {conference},
booktitle = {Proceedings of the 24th ACM International Conference on Information and Knowledge Management (CIKM)},
abstract = {Malicious users are a threat to many sites and defending against them demands innovative countermeasures. When malicious users join sites, they provide limited information about themselves. With this limited information, sites can find it difficult to distinguish between a malicious user and a normal user. In this study, we develop a methodology that identifies malicious users with limited information. As information provided by malicious users can vary, the proposed methodology utilizes minimum information to identify malicious users. It is shown that as little as 10 bits of information can help greatly in this challenging task. The experiments results verify that this methodology is effective in identifying malicious users in the realistic scenario of limited information availability.},
url = {http://www.cikm-2015.org/},
pdf = {files/10Bits.pdf},
}