Epidemic profiles and defense of scale-free networks
Proceedings of the 2003 ACM workshop on Rapid malcode
On instant messaging worms, analysis and countermeasures
Proceedings of the 2005 ACM workshop on Rapid malcode
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Catching instant messaging worms with change-point detection techniques
LEET'08 Proceedings of the 1st Usenix Workshop on Large-Scale Exploits and Emergent Threats
User interactions in social networks and their implications
Proceedings of the 4th ACM European conference on Computer systems
Analyzing patterns of user content generation in online social networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Analysis of a Location-Based Social Network
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Toward worm detection in online social networks
Proceedings of the 26th Annual Computer Security Applications Conference
A note on the spread of worms in scale-free networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Key challenges in defending against malicious socialbots
LEET'12 Proceedings of the 5th USENIX conference on Large-Scale Exploits and Emergent Threats
Containment of misinformation spread in online social networks
Proceedings of the 3rd Annual ACM Web Science Conference
Peri-Watchdog: Hunting for hidden botnets in the periphery of online social networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Analysis of misinformation containment in online social networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
A study on common malware families evolution in 2012
Journal in Computer Virology
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Online social networks, which have been expanding at a blistering speed recently, have emerged as a popular communication infrastructure for Internet users. Meanwhile, malware that specifically target these online social networks are also on the rise. In this work, we aim to investigate the characteristics of malware propagation in online social networks. Our study is based on a dataset collected from a real-world location-based online social network, which includes not only the social graph formed by its users but also the users' activity events. We analyze the social structure and user activity patterns of this network, and confirm that it is a typical online social network, suggesting that conclusions drawn from this specific network can be translated to other online social networks. We use extensive trace-driven simulation to study the impact of initial infection, user click probability, social structure, and activity patterns on malware propagation in online social networks. We also investigate the performance of a few user-oriented and server-oriented defense schemes against malware spreading in online social networks and identify key factors that affect their effectiveness. We believe that this comprehensive study has deepened our understanding of the nature of online social network malware and also shed light on how to defend against them effectively.