Sciweavers

Share
ACSAC
2010
IEEE

Toward worm detection in online social networks

8 years 9 months ago
Toward worm detection in online social networks
Worms propagating in online social networking (OSN) websites have become a major security threat to both the websites and their users in recent years. Since these worms exhibit unique propagation vectors, existing Internet worm detection mechanisms cannot be applied to them. In this work, we propose an early warning OSN worms detection system, which leverages both the propagation characteristics of these worms and the topological properties of online social networks. Our system can effectively monitor the entire social graph by keeping only a small number of user accounts under surveillance. Moreover, the system applies a two-level correlation scheme to reduce the noise from normal user communications such that infected user accounts can be identified with a higher accuracy. Our evaluation on the real social graph data obtained from Flickr indicates
Wei Xu, Fangfang Zhang, Sencun Zhu
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where ACSAC
Authors Wei Xu, Fangfang Zhang, Sencun Zhu
Comments (0)
books