A campaign-based characterization of spamming strategies

5th Conference on Email and Anti-Spam, CEAS 2008

Volumn , Issue , 2008, Pages

  Calais, Pedro H ^a   Pires, Douglas E V ^a   Guedes, Dorgival Olavo ^a   Meira Jr , Wagner ^a   Hoepers, Cristine ^b   Steding Jessen, Klaus ^b  

^a FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^b Computer Emergency Response Team Brazil Network Information Center Brazil ^*  (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATA MINING; SPAMMING;

ASSOCIATION ANALYSIS; CO-OCCURRENCE; FREQUENT PATTERN TREE; NETWORK RESOURCE; RULE MINING ALGORITHMS; SPAM IDENTIFICATION; SPAM MESSAGES; SPAMMERS;

INTERNET;

EID: 84904814245     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Anderson, D. S., Fleizach, C., Savage, S., & Voelker, G. M. (2007). Spamscatter: Characterizing internet scam hosting infrastructure. USENIX Security.
2. Andreolini, M., Bulgarelli, A., Colajanni, M., & Mazzoni, F. (2005). Honeyspam: honeypots fighting spam at the source. SRUTI'05: Proceedings of the Steps to Reducing Unwanted Traffic on the Internet on Steps to Reducing Unwanted Traffic on the Internet Workshop (pp. 11{11). Berkeley, CA, USA: USENIX Association.
3. Cavnar, W., & Trenkle, J. (1994). N-gram-based text categorization. Proceedings of SDAIR-94, 3rd Annual Symposium on Document Analysis and Information Retrieval (pp. 161{175). Las Vegas, US.
4. Cooke, E., Jahanian, F., & McPherson, D. (2005). The zombie roundup: understanding, detecting, and disrupting botnets. SRUTI'05: Proceedings of the Steps to Reducing Unwanted Traffic on the Inter-net on Steps to Reducing Unwanted Traffic on the Internet Workshop (pp. 6{6). Berkeley, CA, USA: USENIX Association.
5. Kolcz, A., & Chowdhury, A. (2007). Hardening fingerprinting by context. Proceedings of the 4th Conference on Email and Anti-Spam (CEAS). Mountain View, CA. Mountain View, CA.
6. Li, F., & Hsieh, M.-H. (2006). An empirical study of clustering behavior of spammers and group-based anti-spam strategies. Proceedings of the Third Conference on Email and Anti-Spam (CEAS). Mountain View, CA.
7. Musat, C. (2006). Layout based spam filtering. Transactions on Engineering, Computing and Technology.
8. Provos, N., & Holz, T. (2007). Virtual honey-pots: From botnet tracking to intrusion detection. Addison-Wesley Professional. 1st edition, ISBN-13: 978-0321336323.
9. Pu, C., & Webb, S. (2006). Observed trends in spam construction techniques: A case study of spam evolution. Proceedings of the 3rd Conference on Email and Anti-Spam (CEAS). Mountain View, CA.
10. Ramachandran, A., & Feamster, N. (2006). Understanding the network-level behavior of spammers. SIGCOMM '06: Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications (pp. 291{302). New York, NY, USA: ACM.
11. Sophos.com (2004). The Spam Economy: The Convergent Spam and Virus Threats. August 2004. http://www.sophos.com/whitepapers/Sophos-spam-economy- wpus.pdf.
12. Steding-Jessen, K., Vijaykumar, N. L., & Montes, A. (2008). Using low-interaction honeypots to study the abuse of open proxies to send spam. To appear in: INFOCOMP Journal of Computer Science.
13. Tan, P., Steinbach, M., & Kumar, V. (2005). Introduction to data mining, (first edition). Addison-Wesley Longman Publishing Co.
14. Wang, Z., Josephson, W., Lv, Q., Charikar, M., & Li, K. (2007). Filtering image spam with nearduplicate detection. Proceedings of the Fourth Conference on Email and Anti-Spam (CEAS). Mountain View, CA. Mountain View, CA.
15. Yeh, C.-C., & Lin, C.-H. (2006). Near-duplicate mail detection based on url information for spam filtering. Information Networking. Advances in Data Communications and Wireless Networks (pp. 842{851). Springer Berlin / Heidelberg. Nível Superior