A taste of tweets

In this paper, through reverse engineering Twitter spammers' tastes (their preferred targets to spam), we aim at providing guidelines for building more effective social honeypots, and generating new insights to defend against social spammers. Specifically, we first perform a measurement study by deploying "benchmark" social honeypots on Twitter with diverse and fine-grained social behavior patterns to trap spammers. After five months' data collection, we make a deep analysis on how Twitter spammers find their targets. Based on the analysis, we evaluate our new guidelines for building effective social honeypots by implementing "advanced" honeypots. Particularly, within the same time period, using those advanced honeypots can trap spammers around 26 times faster than using "traditional" honeypots.