Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiclass Spectral Clustering
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Understanding the network-level behavior of spammers
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
A tutorial on spectral clustering
Statistics and Computing
Statistical properties of community structure in large social and information networks
Proceedings of the 17th international conference on World Wide Web
Self-adjust local connectivity analysis for spectral clustering
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Classification of textual E-mail spam using data mining techniques
Applied Computational Intelligence and Soft Computing
Longtime behavior of harvesting spam bots
Proceedings of the 2012 ACM conference on Internet measurement conference
On spectral partitioning of co-authorship networks
CISIM'12 Proceedings of the 11th IFIP TC 8 international conference on Computer Information Systems and Industrial Management
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To date, most studies on spam have focused only on the spamming phase of the spam cycle and have ignored the harvesting phase, which consists of the mass acquisition of email addresses. It has been observed that spammers conceal their identity to a lesser degree in the harvesting phase, so it may be possible to gain new insights into spammers' behavior by studying the behavior of harvesters, which are individuals or bots that collect email addresses. In this paper, we reveal social networks of spammers by identifying communities of harvesters with high behavioral similarity using spectral clustering. The data analyzed was collected through Project Honey Pot, a distributed system for monitoring harvesting and spamming. Our main findings are (1) that most spammers either send only phishing emails or no phishing emails at all, (2) that most communities of spammers also send only phishing emails or no phishing emails at all, and (3) that several groups of spammers within communities exhibit coherent temporal behavior and have similar IP addresses. Our findings reveal some previously unknown behavior of spammers and suggest that there is indeed social structure between spammers to be discovered.