Spam Short Messages Detection via Mining Social Networks |
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| Authors: | Jian-Yun Liu Yu-Hang Zhao Zhao-Xiang Zhang Yun-Hong Wang Xue-Mei Yuan Lei Hu Zhen-Jiang Dong |
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| Affiliation: | 1. School of Computer Science and Engineering, Beihang University, Beijing, 100191, China
2. ZTE Corporation, Nanjing, 210012, China
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| Abstract: | Short message service (SMS) is now becoming an indispensable way of social communication, and the problem of mobile spam is getting increasingly serious. We propose a novel approach for spam messages detection. Instead of conventional methods that focus on keywords or flow rate filtering, our system is based on mining under a more robust structure: the social network constructed with SMS. Several features, including static features, dynamic features and graph features, are proposed for describing activities of nodes in the network in various ways. Experimental results operated on real dataset prove the validity of our approach. |
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| Keywords: | spam detection social network graph mining |
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