Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Crowdsourcing user studies with Mechanical Turk
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Who are the crowdworkers?: shifting demographics in mechanical turk
CHI '10 Extended Abstracts on Human Factors in Computing Systems
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@spam: the underground on 140 characters or less
Proceedings of the 17th ACM conference on Computer and communications security
Analyzing the Amazon Mechanical Turk marketplace
XRDS: Crossroads, The ACM Magazine for Students - Comp-YOU-Ter
Detecting product review spammers using rating behaviors
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Finding unusual review patterns using unexpected rules
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Detecting and characterizing social spam campaigns
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Detecting spammers on social networks
Proceedings of the 26th Annual Computer Security Applications Conference
Finding deceptive opinion spam by any stretch of the imagination
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Dirty jobs: the role of freelance labor in web service abuse
SEC'11 Proceedings of the 20th USENIX conference on Security
Anatomy of a Crowdsourcing Platform - Using the Example of Microworkers.com
IMIS '11 Proceedings of the 2011 Fifth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing
Suspended accounts in retrospect: an analysis of twitter spam
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Uncovering social network sybils in the wild
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Understanding fraudulent activities in online ad exchanges
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Adapting social spam infrastructure for political censorship
LEET'12 Proceedings of the 5th USENIX conference on Large-Scale Exploits and Emergent Threats
Gender swapping and user behaviors in online social games
Proceedings of the 22nd international conference on World Wide Web
Wisdom in the social crowd: an analysis of quora
Proceedings of the 22nd international conference on World Wide Web
Characterizing and detecting malicious crowdsourcing
Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM
The best answers? think twice: online detection of commercial campaigns in the CQA forums
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Understanding latent interactions in online social networks
ACM Transactions on the Web (TWEB)
Trafficking fraudulent accounts: the role of the underground market in Twitter spam and abuse
SEC'13 Proceedings of the 22nd USENIX conference on Security
You are how you click: clickstream analysis for Sybil detection
SEC'13 Proceedings of the 22nd USENIX conference on Security
Campaign extraction from social media
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
Uncovering social network Sybils in the wild
ACM Transactions on Knowledge Discovery from Data (TKDD) - Casin special issue
Expert Systems with Applications: An International Journal
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Popular Internet services in recent years have shown that remarkable things can be achieved by harnessing the power of the masses using crowd-sourcing systems. However, crowd-sourcing systems can also pose a real challenge to existing security mechanisms deployed to protect Internet services. Many of these security techniques rely on the assumption that malicious activity is generated automatically by automated programs. Thus they would perform poorly or be easily bypassed when attacks are generated by real users working in a crowd-sourcing system. Through measurements, we have found surprising evidence showing that not only do malicious crowd-sourcing systems exist, but they are rapidly growing in both user base and total revenue. We describe in this paper a significant effort to study and understand these "crowdturfing" systems in today's Internet. We use detailed crawls to extract data about the size and operational structure of these crowdturfing systems. We analyze details of campaigns offered and performed in these sites, and evaluate their end-to-end effectiveness by running active, benign campaigns of our own. Finally, we study and compare the source of workers on crowdturfing sites in different countries. Our results suggest that campaigns on these systems are highly effective at reaching users, and their continuing growth poses a concrete threat to online communities both in the US and elsewhere.