The Honeynet Project: Trapping the Hackers
IEEE Security and Privacy
Honeycomb: creating intrusion detection signatures using honeypots
ACM SIGCOMM Computer Communication Review
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Profiles as Conversation: Networked Identity Performance on Friendster
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 03
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Splog detection using self-similarity analysis on blog temporal dynamics
AIRWeb '07 Proceedings of the 3rd international workshop on Adversarial information retrieval on the web
Spam Filtering Using Statistical Data Compression Models
The Journal of Machine Learning Research
Communications of the ACM
Fighting Spam on Social Web Sites: A Survey of Approaches and Future Challenges
IEEE Internet Computing
Knowledge sharing and yahoo answers: everyone knows something
Proceedings of the 17th international conference on World Wide Web
Unveiling facebook: a measurement study of social network based applications
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement
Email Spam Filtering: A Systematic Review
Foundations and Trends in Information Retrieval
Social networks and context-aware spam
Proceedings of the 2008 ACM conference on Computer supported cooperative work
Proceedings of the 18th international conference on World wide web
Detecting spammers and content promoters in online video social networks
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
@spam: the underground on 140 characters or less
Proceedings of the 17th ACM conference on Computer and communications security
You are where you tweet: a content-based approach to geo-locating twitter users
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Let web spammers expose themselves
Proceedings of the fourth ACM international conference on Web search and data mining
Spammers' networks within online social networks: a case-study on Twitter
Proceedings of the 20th international conference companion on World wide web
Detecting malicious web links and identifying their attack types
WebApps'11 Proceedings of the 2nd USENIX conference on Web application development
Semantic enrichment of twitter posts for user profile construction on the social web
ESWC'11 Proceedings of the 8th extended semantic web conference on The semanic web: research and applications - Volume Part II
I want to answer; who has a question?: Yahoo! answers recommender system
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Phi.sh/$oCiaL: the phishing landscape through short URLs
Proceedings of the 8th Annual Collaboration, Electronic messaging, Anti-Abuse and Spam Conference
Suspended accounts in retrospect: an analysis of twitter spam
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Detecting collective attention spam
Proceedings of the 2nd Joint WICOW/AIRWeb Workshop on Web Quality
Spam filtering in twitter using sender-receiver relationship
RAID'11 Proceedings of the 14th international conference on Recent Advances in Intrusion Detection
Die free or live hard? empirical evaluation and new design for fighting evolving twitter spammers
RAID'11 Proceedings of the 14th international conference on Recent Advances in Intrusion Detection
Proceedings of the 21st international conference on World Wide Web
A framework for unsupervised spam detection in social networking sites
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Poultry markets: on the underground economy of twitter followers
Proceedings of the 2012 ACM workshop on Workshop on online social networks
Modeling user posting behavior on social media
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Efficient and scalable socware detection in online social networks
Security'12 Proceedings of the 21st USENIX conference on Security symposium
Poultry markets: on the underground economy of twitter followers
ACM SIGCOMM Computer Communication Review - Special october issue SIGCOMM '12
Robust detection of comment spam using entropy rate
Proceedings of the 5th ACM workshop on Security and artificial intelligence
Observing common spam in Twitter and email
Proceedings of the 2012 ACM conference on Internet measurement conference
A content-driven framework for geolocating microblog users
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
Twitter games: how successful spammers pick targets
Proceedings of the 28th Annual Computer Security Applications Conference
TweoLocator: a non-intrusive geographical locator system for Twitter
Proceedings of the 5th ACM SIGSPATIAL International Workshop on Location-Based Social Networks
Detecting malicious tweets in trending topics using a statistical analysis of language
Expert Systems with Applications: An International Journal
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Detecting tip spam in location-based social networks
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Searching for spam: detecting fraudulent accounts via web search
PAM'13 Proceedings of the 14th international conference on Passive and Active Measurement
Multi-source deep learning for information trustworthiness estimation
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Detection of spam tipping behaviour on foursquare
Proceedings of the 22nd international conference on World Wide Web companion
An analysis of socware cascades in online social networks
Proceedings of the 22nd international conference on World Wide Web
Community-based features for identifying spammers in online social networks
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Analysis and identification of spamming behaviors in Sina Weibo microblog
Proceedings of the 7th Workshop on Social Network Mining and Analysis
Follow the green: growth and dynamics in twitter follower markets
Proceedings of the 2013 conference on Internet measurement conference
UNIK: unsupervised social network spam detection
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Behavior analysis of low-literate users of a viral speech-based telephone service
Proceedings of the 4th Annual Symposium on Computing for Development
Social spammer detection in microblogging
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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
Proceedings of the 19th international conference on Intelligent User Interfaces
Twitter n-gram corpus with demographic metadata
Language Resources and Evaluation
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Web-based social systems enable new community-based opportunities for participants to engage, share, and interact. This community value and related services like search and advertising are threatened by spammers, content polluters, and malware disseminators. In an effort to preserve community value and ensure longterm success, we propose and evaluate a honeypot-based approach for uncovering social spammers in online social systems. Two of the key components of the proposed approach are: (1) The deployment of social honeypots for harvesting deceptive spam profiles from social networking communities; and (2) Statistical analysis of the properties of these spam profiles for creating spam classifiers to actively filter out existing and new spammers. We describe the conceptual framework and design considerations of the proposed approach, and we present concrete observations from the deployment of social honeypots in MySpace and Twitter. We find that the deployed social honeypots identify social spammers with low false positive rates and that the harvested spam data contains signals that are strongly correlated with observable profile features (e.g., content, friend information, posting patterns, etc.). Based on these profile features, we develop machine learning based classifiers for identifying previously unknown spammers with high precision and a low rate of false positives.