Machine Learning
Communications of the ACM
Proceedings of the first workshop on Online social networks
Social networks and context-aware spam
Proceedings of the 2008 ACM conference on Computer supported cooperative work
All your contacts are belong to us: automated identity theft attacks on social networks
Proceedings of the 18th international conference on World wide web
A social-engineering-centric data collection initiative to study phishing
Proceedings of the First Workshop on Building Analysis Datasets and Gathering Experience Returns for Security
Reverse social engineering attacks in online social networks
DIMVA'11 Proceedings of the 8th international conference on Detection of intrusions and malware, and vulnerability assessment
Spam detection on twitter using traditional classifiers
ATC'11 Proceedings of the 8th international conference on Autonomic and trusted 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
The socialbot network: when bots socialize for fame and money
Proceedings of the 27th Annual Computer Security Applications Conference
Poster: online spam filtering in social networks
Proceedings of the 18th ACM conference on Computer and communications security
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
Serf and turf: crowdturfing for fun and profit
Proceedings of the 21st international conference on World Wide Web
Key challenges in defending against malicious socialbots
LEET'12 Proceedings of the 5th USENIX conference on Large-Scale Exploits and Emergent Threats
Adapting social spam infrastructure for political censorship
LEET'12 Proceedings of the 5th USENIX conference on Large-Scale Exploits and Emergent Threats
Poultry markets: on the underground economy of twitter followers
Proceedings of the 2012 ACM workshop on Workshop on online social networks
Information credibility on twitter in emergency situation
PAISI'12 Proceedings of the 2012 Pacific Asia conference on Intelligence and Security Informatics
Detecting social spam campaigns on twitter
ACNS'12 Proceedings of the 10th international conference on Applied Cryptography and Network Security
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
Proceedings of the CUBE International Information Technology Conference
Twitter games: how successful spammers pick targets
Proceedings of the 28th Annual Computer Security Applications Conference
Fluxing botnet command and control channels with URL shortening services
Computer Communications
Detecting malicious tweets in trending topics using a statistical analysis of language
Expert Systems with Applications: An International Journal
Design and analysis of a social botnet
Computer Networks: The International Journal of Computer and Telecommunications Networking
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Searching for spam: detecting fraudulent accounts via web search
PAM'13 Proceedings of the 14th international conference on Passive and Active Measurement
An analysis of socware cascades in online social networks
Proceedings of the 22nd international conference on World Wide Web
Two years of short URLs internet measurement: security threats and countermeasures
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
REPLOT: REtrieving profile links on Twitter for suspicious networks detection
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
Tweeting under pressure: analyzing trending topics and evolving word choice on sina weibo
Proceedings of the first ACM conference on Online social networks
On the hardness of evading combinations of linear classifiers
Proceedings of the 2013 ACM workshop on Artificial intelligence and security
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
Uncovering social network Sybils in the wild
ACM Transactions on Knowledge Discovery from Data (TKDD) - Casin special issue
Stranger danger: exploring the ecosystem of ad-based URL shortening services
Proceedings of the 23rd international conference on World wide web
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Social networking has become a popular way for users to meet and interact online. Users spend a significant amount of time on popular social network platforms (such as Facebook, MySpace, or Twitter), storing and sharing a wealth of personal information. This information, as well as the possibility of contacting thousands of users, also attracts the interest of cybercriminals. For example, cybercriminals might exploit the implicit trust relationships between users in order to lure victims to malicious websites. As another example, cybercriminals might find personal information valuable for identity theft or to drive targeted spam campaigns. In this paper, we analyze to which extent spam has entered social networks. More precisely, we analyze how spammers who target social networking sites operate. To collect the data about spamming activity, we created a large and diverse set of "honey-profiles" on three large social networking sites, and logged the kind of contacts and messages that they received. We then analyzed the collected data and identified anomalous behavior of users who contacted our profiles. Based on the analysis of this behavior, we developed techniques to detect spammers in social networks, and we aggregated their messages in large spam campaigns. Our results show that it is possible to automatically identify the accounts used by spammers, and our analysis was used for take-down efforts in a real-world social network. More precisely, during this study, we collaborated with Twitter and correctly detected and deleted 15,857 spam profiles.