IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Sybilproof reputation mechanisms
Proceedings of the 2005 ACM SIGCOMM workshop on Economics of peer-to-peer systems
MailRank: using ranking for spam detection
Proceedings of the 14th ACM international conference on Information and knowledge management
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
SybilGuard: defending against sybil attacks via social networks
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Combating web spam with trustrank
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
SybilLimit: A Near-Optimal Social Network Defense against Sybil Attacks
SP '08 Proceedings of the 2008 IEEE Symposium on Security and Privacy
All your contacts are belong to us: automated identity theft attacks on social networks
Proceedings of the 18th international conference on World wide web
Parallel community detection on large networks with propinquity dynamics
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Sybil-resilient online content voting
NSDI'09 Proceedings of the 6th USENIX symposium on Networked systems design and implementation
BotGraph: large scale spamming botnet detection
NSDI'09 Proceedings of the 6th USENIX symposium on Networked systems design and implementation
Sybilproof transitive trust protocols
Proceedings of the 10th ACM conference on Electronic commerce
DSybil: Optimal Sybil-Resistance for Recommendation Systems
SP '09 Proceedings of the 2009 30th IEEE Symposium on Security and Privacy
You are who you know: inferring user profiles in online social networks
Proceedings of the third ACM international conference on Web search and data mining
CAPTCHA: using hard AI problems for security
EUROCRYPT'03 Proceedings of the 22nd international conference on Theory and applications of cryptographic techniques
Sybil attacks against mobile users: friends and foes to the rescue
INFOCOM'10 Proceedings of the 29th conference on Information communications
Outside the Closed World: On Using Machine Learning for Network Intrusion Detection
SP '10 Proceedings of the 2010 IEEE Symposium on Security and Privacy
An analysis of social network-based Sybil defenses
Proceedings of the ACM SIGCOMM 2010 conference
Whanau: a sybil-proof distributed hash table
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
WOSN'10 Proceedings of the 3rd conference on Online social networks
Detecting and characterizing social spam campaigns
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Measuring the mixing time of social graphs
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Bazaar: strengthening user reputations in online marketplaces
Proceedings of the 8th USENIX conference on Networked systems design and implementation
Proceedings of the 4th Workshop on Social Network Systems
Preventing Sybil Attacks by Privilege Attenuation: A Design Principle for Social Network Systems
SP '11 Proceedings of the 2011 IEEE Symposium on Security and Privacy
Limiting large-scale crawls of social networking sites
Proceedings of the ACM SIGCOMM 2011 conference
Dirty jobs: the role of freelance labor in web service abuse
SEC'11 Proceedings of the 20th USENIX conference on Security
Sybil defenses via social networks: a tutorial and survey
ACM SIGACT News
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
The socialbot network: when bots socialize for fame and money
Proceedings of the 27th Annual Computer Security Applications Conference
Innocent by association: early recognition of legitimate users
Proceedings of the 2012 ACM conference on Computer and communications security
Facilitating real-time graph mining
Proceedings of the fourth international workshop on Cloud data management
Design and analysis of a social botnet
Computer Networks: The International Journal of Computer and Telecommunications Networking
Graph-based Sybil detection in social and information systems
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)
Using naive bayes to detect spammy names in social networks
Proceedings of the 2013 ACM workshop on Artificial intelligence and security
You are how you click: clickstream analysis for Sybil detection
SEC'13 Proceedings of the 22nd USENIX conference on Security
Leveraging Social Feedback to Verify Online Identity Claims
ACM Transactions on the Web (TWEB)
Uncovering social network Sybils in the wild
ACM Transactions on Knowledge Discovery from Data (TKDD) - Casin special issue
Fake View Analytics in Online Video Services
Proceedings of Network and Operating System Support on Digital Audio and Video Workshop
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Users increasingly rely on the trustworthiness of the information exposed on Online Social Networks (OSNs). In addition, OSN providers base their business models on the marketability of this information. However, OSNs suffer from abuse in the form of the creation of fake accounts, which do not correspond to real humans. Fakes can introduce spam, manipulate online rating, or exploit knowledge extracted from the network. OSN operators currently expend significant resources to detect, manually verify, and shut down fake accounts. Tuenti, the largest OSN in Spain, dedicates 14 full-time employees in that task alone, incurring a significant monetary cost. Such a task has yet to be successfully automated because of the difficulty in reliably capturing the diverse behavior of fake and real OSN profiles. We introduce a new tool in the hands of OSN operators, which we call SybilRank. It relies on social graph properties to rank users according to their perceived likelihood of being fake (Sybils). SybilRank is computationally efficient and can scale to graphs with hundreds of millions of nodes, as demonstrated by our Hadoop prototype. We deployed SybilRank in Tuenti's operation center. We found that ∼90% of the 200K accounts that SybilRank designated as most likely to be fake, actually warranted suspension. On the other hand, with Tuenti's current user-report-based approach only ∼5% of the inspected accounts are indeed fake.