In consideration with the security of user on the Internet, Phishing remains an important threat. Currently working systems are based on reactive URL blacklisting technique which is inefficient due to short lifetime of Phishing websites and unavailability of newly launched Phishing sites. In the proposed system we introduce a real-time automated phishing detection system for e-mails which can analyze an URL present in the context of an e-mail to identify potential Phishing sites. Along with the URL, contents of emails are also checked with intra-URL relatedness. Phishing URL's have relationships between their first part (lower domain) and remaining part (upper domain) like path, file folder, etc. URL uniqueness is figured out by evaluating it using identical properties extracted from keywords that compose a URL based on the query data from Google and Yahoo search engines

1. S. Marchal, J. François, R. State, and T. Engel, "PhishScore: Hacking phishers minds," in Proc. 10th Int. CNSM, 2014, pp. 46–54.
2. Yanhui Du, Fu Xue "Research of the Anti-Phishing Technology based on E-mail extraction and analysis. "
3. Samuel Marchal, Jérôme François, Radu State, and Thomas Engel "PhishStorm: Detecting With Streaming Analytics"
4. T. Segaran and J. Hammerbacher, "Beautiful Data: The Stories Behind Elegant Data Solutions. "Sebastopol, CA, USA: O'Reilly Media, 2009.
5. M. Bellare and A. Palacio. Gq and schnorr identification schemes: Proofs of security against impersonation under active and concurrent attacks. In CRYPTO, pages 162–177, 2002.
6. S. Marchal, J. François, R. State, and T. Engel, "Proactive discovery of phishing related domain names,"in Research in Attacks, Intrusions, and Defenses. New York, NY, USA: Springer-Verlag, 2012, pp. 190–209
7. M. Hall et al. , "The WEKA data mining software: An update,"ACM SIGKDD Explorations Newslett. , vol. 11, no. 1, pp. 10–18, Jun. 2009.
8. A. Le, A. Markopoulou, and M. Faloutsos, "PhishDef: URL names say it all," in Proc. IEEE INFOCOM, 2011, pp. 191–195.
9. E. Medvet, E. Kirda, and C. Kruegel, "Visual-similarity-based phishingdetection," in Proc. 4th Int. Conf. Security Privacy Commun. Netw. , 2008,pp. 1–6, ACM.
10. J. Ma, L. K. Saul, S. Savage, and G. M. Voelker, "Beyond blacklists:Learning to detect malicious web sites from suspicious URLs," in Proc. 15th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, 2009, pp. 1245–1254, ACM.
11. J. Zhang, P. Porras, and J. Ullrich, "Highly predictive blacklisting," inProc. 17thConf. Security Symp. , 2008, pp. 107–122,USENIXAssociation.

Intra-url Relatedness Mails Phishing Detection Lower Domain Upper Domain.