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Abstract: Critical functionality and huge influence of the hot trend/topic page (HTP) in microblogging sites have driven the creation of a new kind of underground service called the bogus traffic service (BTS). BTS provides a kind of illegal service which hijacks the HTP by pushing the controlled topics into it for malicious customers with the goal of guiding public opinions. To hijack HTP, the agents of BTS maintain an army of black-market accounts called bogus traffic accounts (BTAs) and control BTAs to generate a burst of fake traffic by massively retweeting the tweets containing the customer desired topic (hashtag). Although this service has been extensively exploited by malicious customers, little has been done to understand it. In this paper, we conduct a systematic measurement study of the BTS. We first investigate and collect 125 BTS agents from a variety of sources and set up a honey pot account to capture BTAs from these agents. We then build a BTA detector that detects 162 218 BTAs from Weibo, the largest Chinese microblogging site, with a precision of 94.5%. We further use them as a bridge to uncover 296 916 topics that might be involved in bogus traffic. Finally, we uncover the operating mechanism from the perspectives of the attack cycle and the attack entity. The highlights of our findings include the temporal attack patterns and intelligent evasion tactics of the BTAs. These findings bring BTS into the spotlight. Our work will help in understanding and ultimately eliminating this threat.

在线社交网络中的虚假流量服务挖掘

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