Lexical URL analysis for discriminating phishing and legitimate e-mail messages

2011 International Conference for Internet Technology and Secured Transactions, ICITST 2011

Volumn , Issue , 2011, Pages 422-427

  Khonji, Mahmoud ^a   Iraqi, Youssef ^a   Jones, Andrew ^a,b  

^a KHALIFA UNIVERSITY   (United Arab Emirates)

^b EDITH COWAN UNIVERSITY   (Australia)

Author keywords

emails; lexical analysis; phishing attacks; URLs

Indexed keywords

ANALYSIS APPROACH; ANTI-PHISHING; CLASSIFICATION ACCURACY; EMAIL CLASSIFICATION; EMAIL MESSAGES; EMAILS; LEXICAL ANALYSIS; MALWARES; PHISHING; PHISHING ATTACKS;

ELECTRONIC MAIL; INTERNET; WEBSITES;

COMPUTER CRIME;

EID: 84857472534     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. A.-P. W. G. (APWG), "Phishing activity trends report," http://www.antiphishing.org/reports/apwg-report-Q3-2009.pdf, 3rd Quarter 2009.
2. "Trojan.Spyeye j symantec," http://www.symantec.com/security response/ writeup.jsp?docid=2010-020216-0135-99, accessed January 2011.
3. A. Alnajim and M. Munro, "An evaluation of users' anti-phishing knowledge retention," in Information Management and Engineering, 2009. ICIME '09. International Conference on, April 2009, pp. 210-214.
4. G. Gaffney, "The myth of the stupid user," http://www. infodesign.com.au/articles/themythofthestupiduser, accessed March 2011.
5. M. Khonji, Y. Iraqi, and A. Jones, "Lexical url analysis for discriminating phishing and legitimate websites," in Proceedings of the 8th Annual Collaboration, Electronic messaging, Anti-Abuse and Spam Conference, ser. CEAS '11. New York, NY, USA: ACM, 2011, pp. 109-115. [Online]. Available: http://doi.acm.org/10.1145/2030376.2030389
6. S. Sheng, B. Wardman, G. Warner, L. F. Cranor, J. Hong, and C. Zhang, "An empirical analysis of phishing blacklists," http://ceas.cc/2009/ papers/ceas2009-paper-32.pdf, 2009.
7. I. Fette, N. Sadeh, and A. Tomasic, "Learning to detect phishing emails,"in Proceedings of the 16th international conference on World Wide Web, ser. WWW '07. New York, NY, USA: ACM, 2007, pp. 649-656. [Online]. Available: http://doi.acm.org/10.1145/1242572.1242660
8. J. Nazario, "Phishing corpus," http://monkey.org/~jose/wiki/ doku.php?id=phishingcorpus, accessed July 2010.
9. SpamAssassin, "Public corpus," http://spamassassin.apache.org/ publiccorpus/, accessed January 2011. [Online]. Available: http://spamassassin. apache.org/publiccorpus/
10. A. Bergholz, J. De Beer, S. Glahn, M.-F. Moens, G. Paaß, and S. Strobel, "New filtering approaches for phishing email," J. Comput. Secur., vol. 18, pp. 7-35, January 2010. [Online]. Available: http://portal.acm.org/citation.cfm?id=1734234.1734239
11. F. Toolan and J. Carthy, "Phishing detection using classifier ensembles,"in eCrime Researchers Summit, 2009. eCRIME '09., 20 2009.
12. L. Cranor, S. Egelman, J. Hong, and Y. Zhang, "Phinding phish: An evaluation of anti-phishing toolbars," www.cylab.cmu.edu/files/ cmucylab06018.pdf, 2006.
13. M. Khonji, A. Jones, and Y. Iraqi, "A study of feature subset evaluators and feature subset searching methods for phishing classification," in Proceedings of the 8th Annual Collaboration, Electronic messaging, Anti-Abuse and Spam Conference, ser. CEAS '11. New York, NY, USA: ACM, 2011, pp. 135-144. [Online]. Available: http://doi.acm.org/10.1145/2030376. 2030392
14. S. Abu-Nimeh, D. Nappa, X. Wang, and S. Nair, "A comparison of machine learning techniques for phishing detection," in Proceedings of the anti-phishing working groups 2nd annual eCrime researchers summit, ser. eCrime '07. New York, NY, USA: ACM, 2007, pp. 60-69. [Online]. Available: http://doi.acm.org/10.1145/1299015.1299021
15. F. Toolan and J. Carthy, "Feature selection for spam and phishing detection," in eCrime Researchers Summit (eCrime), 2010, ser. eCrime '10, Dallas, TX, 2010.
16. W. N. Gansterer and D. Pölz, "E-mail classification for phishing defense," in Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval, ser. ECIR '09. Berlin, Heidelberg: Springer-Verlag, 2009, pp. 449-460. [Online]. Available: http://dx.doi.org/10.1007/978-3-642-00958-7 40
17. I. H. Witten, E. Frank, and M. A. Hall, Data Mining: Practical Machine Learning Tools and Techniques (Third Edition). San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2011.
18. E. Alpaydin, "Introduction to machine learning," Knowl. Eng. Rev., vol. 20, pp. 432-433, December 2005.