@inproceedings{1b1ca3f6ff8e45aa9b788f174269269f,
title = "Abnormal user detection based on instant messages",
abstract = "Instant messaging (IM) tools have been widely used in peoples' daily life. We study how to detect the identities of IM users from their chatting text. The abnormal detection model is employed to detect the identities of IM users. We use the topic model to find the relations between function words of chatting text, and extract the topic features to represent chatting text To improve the accuracy, we combine topic features with word based features to train the detection model, and achieve good experimental results.",
keywords = "Chatting text, Information retrieval, Instant messaging, Intrusion detection, Security",
author = "Wei Dai and Ding, \{Yu Xin\} and Chenglong Xue and Yibin Zhang and Guohua Wu",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 13th International Conference on Machine Learning and Cybernetics, ICMLC 2014 ; Conference date: 13-07-2014 Through 16-07-2014",
year = "2014",
month = jan,
day = "13",
doi = "10.1109/ICMLC.2014.7009717",
language = "英语",
series = "Proceedings - International Conference on Machine Learning and Cybernetics",
publisher = "IEEE Computer Society",
pages = "831--837",
booktitle = "Proceedings of 2014 International Conference on Machine Learning and Cybernetics, ICMLC 2014",
address = "美国",
}