[1] Robert J. Hall, “How to avoid unwanted email”, COMMUNICATIONS OF THE ACM, Vol. 41, No.3, March 1998.
[2] http://members.aol.com/emailfaq/emailfaq.html#3e
[3] Flavio D. Garcia, “Jaap-Henk Hoepman, Jeroen van Nieuwenhuizen”, SPAM FILTER ANALYSIS, Submitted to SEC 2004.
[4] Open WebMail project available at http://openwebmail.org/
[5] Sendmail available at http://www.sendmail.org/
[6] Postfix available at http://www.postfix.org/
[7] Qmail available at http://www.qmail.org/
[8] J. Myers, “Post Office Protocol – Version 3”, RFC1939, May 1996.
[9] M. Crispin, “Internet Message Access Protocol”, RFC2060, December 1996.
[10] SpamAssassin available at http://spamassassin.apache.org/
[11] TDMA (Tagged Message Deliver Agent) available at http://tmda.net/
[12] Georgios Sakkis, Ion Androutsopoulos, Georgios Paliouras, Vangelis Karkaletsis, Constantine D. Spyropoulos, and Panagiotis Stamatopoulos, “A Memory-Based Approach to Anti-Spam Filtering”, National Centre for Scientific Research(NCSR) Demokritos, Technical Report Demo, 2001.
[13] Paul Graham, ”a Plan for Spam”, available at http://www.paulgraham.com/spam.html
[14] Bayesian available at http://www.bayesian.org/
[15] Ion Androutsopoulos, John Koutsias, Konstantinos V. Chandrinos, Constantine D.Spyropoulos, “An experimental comparison of naive Bayesian and keyword-based anti-spam filtering with personal e-mail messages”, in Proc. the 23rd annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR2000), Athens, Greece, pp. 160-167.
[16] Ion. Androutsopoulos, G.eorgios Paliouras, Vangelis Karkaletsis, Georgios Sakkis, Constantine D. Spyropoulos and Panagiotis Stamatopoulos, “Learning to Filter Spam E-Mail: A Comparison of a Naive Bayesian and a Memory-Based Approach” In H. Zaragoza, P. Gallinari, and M. Rajman (Eds.), Proc. Workshop on Machine Learning and Textual Information Access, 4th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD 2000), Lyon, France, pp. 1-13, 2000.
[17] POPFile available at http://popfile.sourceforge.net/
[18] RFC822 available at http://www.faqs.org/rfcs/rfc822.html
[19] Spamkiller for MailServers available at http://www.nai.com/us/products/mcafee/antispam/spk_mailserver.htm
[20] No Spam Today! for Workstations available at http://www.nospamtoday.com/workstation/
[21] Pop3proxy available at http://mcd.perlmonk.org/pop3proxy/
[22] Spamkiller Appliances available at http://www.nai.com/us/products/mcafee/antispam/spk_appliances.htm
[23] Abdur Chowdhury, Ophir Frieder, David Grossman, and Mary Catherine McCabe, “Collection Statistics for Fast Duplicate Document Detection”, ACM Transactions on Information Systems, Vol. 20, No. 2, April 2002, Pages 171-191.
[24] Saul Schleimer, Daniel S. Wilkerson, and Alex Aiken, “Winnowing: Local Algorithms for Document Fingerprinting”, SIGMOD 2003, June 9-12, 2003, San Diego, CA.
[25] 葉迺瑋,相似郵件偵測系統設計與實作,國立台灣海洋大學資訊工程學系碩士學位論文,九十三年六月。[26] E. Damiani, S. De Capitani di Vimercati, S. Paraboschi, and P. Samarati, “An Open Digest-based Technique for Spam Detection”, In Proceedings of the 4th IEEE international conference on peer-to-peer computing, 2004.
[27] Shane Hird, Technical Solutions for Controlling Spam, Distributed Systems Technology Center, available at http://security.dstc.edu.au/papers/technical_spam.pdf
[28] Distributed Checksum Clearinghouse (DCC), available at: http://www.rhyolite.com/anti-spam/dcc/
[29] D. Fetterly, M. Manasse, and M. Najork.,” On the evolution of clusters of near-duplicate web pages.,” in Proceedings of the 1st Latin American Web Congress, pages 37-45, 2003.
[30] Mehran Sahami, Susan Dumaisy, David Heckermany, Eric Horvitzy, “A Bayesian approach to filtering junk E-Mail” in Proc. Of AAAI Workshop on Learning for Text Categorization, July 1998, Madison, Wisconsin.
[31] Simon Tong, and Daphne Koller, “Support Vector Machine Active Learning with Applications to Text Classification”, Journal of Machine Learning Research, vol. 2, pp.45-66, 2001.
[32] Klaus-Robust Mueller, et al. “An introduction to kernel-based learning algorithms”, IEEE Transactions on Neural Networks, March 2001.
[33] J.R. Quinlan, “C4.5: Programs for Machine Learning”, San Mateo, Calif.: Morgan Kaufmann Publishers, 1993.
[34] Fernando J. Corbato, “On computer system challenges”, JACM, 50(1):30-31, January 2003.
[35] S. Olsen, “Spam: It's completely out of control”, CNET News.com, March 21 2002. Available: http://zdnet.com.com/2100-1106-865442.html.
[36] Geoff Hulten, Anthony Penta, Gopalakrishnan Seshadrinathan, Manav Mishra, “Trends in Spam Products and Methods “, First Conference on Email and Anti-Spam (CEAS), Mountain View, CA ,July 30 and 31, 2004.
[37] S. Machlis, “Uh-oh: Spam's getting more sophisticated”,Computerworld, Jan 17 2003.
[38] John Graham-Cumming, “How to beat an adaptive spam filter”, MIT Spam Conference, 2004.
[39] Gregory L. Wittel and S. Felix Wu, “On attacking statistical spam filters”, in Proceedings of CEAS04.
[40] RFC 2045 available at ftp://ftp.rfc-editor.org/in-notes/rfc2045.txt
[41] RFC 2046 available at ftp://ftp.rfc-editor.org/in-notes/rfc2046.txt
[42] RFC 2047 available at ftp://ftp.rfc-editor.org/in-notes/rfc2047.txt
[43] RFC 2048 available at ftp://ftp.rfc-editor.org/in-notes/rfc2048.txt
[44] RFC 2049 available at ftp://ftp.rfc-editor.org/in-notes/rfc2049.txt
[45] K-Nearest Neighbor available at http://blue.lins.fju.edu.tw/~tseng/ResearchResults/categorization.htm
[46] Nearest Neighbor available at http://www.cs.umd.edu/~brabec/quadtree/nearest.htm