Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Fighting Spam on Social Web Sites: A Survey of Approaches and Future Challenges
IEEE Internet Computing
Identifying suspicious URLs: an application of large-scale online learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
A survey of learning-based techniques of email spam filtering
Artificial Intelligence Review
CAPTCHA: using hard AI problems for security
EUROCRYPT'03 Proceedings of the 22nd international conference on Theory and applications of cryptographic techniques
Detecting spammers with SNARE: spatio-temporal network-level automatic reputation engine
SSYM'09 Proceedings of the 18th conference on USENIX security symposium
Limiting large-scale crawls of social networking sites
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A social-spam detection framework
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The socialbot network: when bots socialize for fame and money
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Canal: scaling social network-based Sybil tolerance schemes
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Online social network platforms: toward a model-backed security evaluation
Proceedings of the 1st Workshop on Privacy and Security in Online Social Media
The role of social networks in information diffusion
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Aiding the detection of fake accounts in large scale social online services
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Key challenges in defending against malicious socialbots
LEET'12 Proceedings of the 5th USENIX conference on Large-Scale Exploits and Emergent Threats
Efficient and scalable socware detection in online social networks
Security'12 Proceedings of the 21st USENIX conference on Security symposium
The devil is in the (implementation) details: an empirical analysis of OAuth SSO systems
Proceedings of the 2012 ACM conference on Computer and communications security
Defending against large-scale crawls in online social networks
Proceedings of the 8th international conference on Emerging networking experiments and technologies
Computer Networks: The International Journal of Computer and Telecommunications Networking
Design and analysis of a social botnet
Computer Networks: The International Journal of Computer and Telecommunications Networking
Maygh: building a CDN from client web browsers
Proceedings of the 8th ACM European Conference on Computer Systems
CopyCatch: stopping group attacks by spotting lockstep behavior in social networks
Proceedings of the 22nd international conference on World Wide Web
Homing socialbots: intrusion on a specific organization's employee using Socialbots
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Approaches to adversarial drift
Proceedings of the 2013 ACM workshop on Artificial intelligence and security
Uncovering social network Sybils in the wild
ACM Transactions on Knowledge Discovery from Data (TKDD) - Casin special issue
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Popular Internet sites are under attack all the time from phishers, fraudsters, and spammers. They aim to steal user information and expose users to unwanted spam. The attackers have vast resources at their disposal. They are well-funded, with full-time skilled labor, control over compromised and infected accounts, and access to global botnets. Protecting our users is a challenging adversarial learning problem with extreme scale and load requirements. Over the past several years we have built and deployed a coherent, scalable, and extensible realtime system to protect our users and the social graph. This Immune System performs realtime checks and classifications on every read and write action. As of March 2011, this is 25B checks per day, reaching 650K per second at peak. The system also generates signals for use as feedback in classifiers and other components. We believe this system has contributed to making Facebook the safest place on the Internet for people and their information. This paper outlines the design of the Facebook Immune System, the challenges we have faced and overcome, and the challenges we continue to face.