Title
Characterizing and detecting malicious crowdsourcing
Abstract
Popular Internet services in recent years have shown that remarkable things can be achieved by harnessing the power of the masses. However, crowd-sourcing systems also pose a real challenge to existing security mechanisms deployed to protect Internet services, particularly those tools that identify malicious activity by detecting activities of automated programs such as CAPTCHAs. In this work, we leverage access to two large crowdturfing sites to gather a large corpus of ground-truth data generated by crowdturfing campaigns. We compare and contrast this data with "organic" content generated by normal users to identify unique characteristics and potential signatures for use in real-time detectors. This poster describes first steps taken focused on crowdturfing campaigns targeting the Sina Weibo microblogging system. We describe our methodology, our data (over 290K campaigns, 34K worker accounts, 61 million tweets...), and some initial results.
Year
DOI
Venue
2013
10.1145/2486001.2491719
SIGCOMM
Keywords
Field
DocType
sina weibo microblogging system,crowd-sourcing system,popular internet service,automated program,large crowdturfing site,existing security mechanism,internet service,large corpus,crowdturfing campaign,malicious crowdsourcing,ground-truth data
World Wide Web,Social media,Computer security,Crowdsourcing,Computer science,Microblogging,CAPTCHA,The Internet
Conference
Volume
Issue
ISSN
43
4
0146-4833
Citations 
PageRank 
References 
1
0.37
4
Authors
5
Name
Order
Citations
PageRank
Tianyi Wang129427.78
Gang Wang246525.30
Xing Li369892.13
Zheng Hai-Tao414224.39
Ben Y. Zhao56274490.12