On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Understanding the network-level behavior of spammers
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Graph evolution: Densification and shrinking diameters
ACM Transactions on Knowledge Discovery from Data (TKDD)
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Analyzing the Structure and Evolution of Massive Telecom Graphs
IEEE Transactions on Knowledge and Data Engineering
Spamalytics: an empirical analysis of spam marketing conversion
Proceedings of the 15th ACM conference on Computer and communications security
Incremental SVM Model for Spam Detection on Dynamic Email Social Networks
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Power-Law Distributions in Empirical Data
SIAM Review
On collection of large-scale multi-purpose datasets on internet backbone links
Proceedings of the First Workshop on Building Analysis Datasets and Gathering Experience Returns for Security
OddBall: spotting anomalies in weighted graphs
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Early detection of outgoing spammers in large-scale service provider networks
DIMVA'13 Proceedings of the 10th international conference on Detection of Intrusions and Malware, and Vulnerability Assessment
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Identifying unsolicited email based on their network-level behavior rather than their content have received huge interest. In this study, we investigate the social network properties of large-scale email networks generated from real email traffic to reveal the properties that are indicative of spam as opposed to the expected legitimate behavior. By analyzing the structural and temporal properties of the email networks we confirm that legitimate email traffic generates a small-world, scale-free network similar to other social networks. However, email traffic as a whole contains unsolicited email, thus the structure of email networks deviates from that of social networks. Our study points out the distinctive characteristics of spam traffic and reveals that the anomalies in the structural properties of email networks are due to the unsocial behavior of spam.