Phishing Email Filtering Techniques A Survey
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2014 by IJCTT Journal|
|Year of Publication : 2014|
|Authors : P.Rohini , K.Ramya|
|DOI : 10.14445/22312803/IJCTT-V17P105|
P.Rohini , K.Ramya. "Phishing Email Filtering Techniques A Survey ". International Journal of Computer Trends and Technology (IJCTT) V17(1):18-21, Nov 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
The most interesting species of Internet fraud is Phishing. Email Phishing is a vulnerable activity which is referred as E-mail fraud, includes web link or form and Asks for confidential information such as password, account details. The email will be classified as phishing email and legitimate email by various phishing email filter techniques based on their functional activities. Various Anti phishing Mechanisms and tools are used for user’s protection against this fraudulent act by using heuristics method and machine learning algorithm by (SVM) support vector machine classifier. The phishing problem is highly effective and no single solution exists to mitigate all the vulnerabilities effectively. This survey relies on recently developed anti phishing mechanisms and tools.
 Personalized Sign-In Seal – Yahoo Inc. https://protect.login.yahoo.com.Accessed: May 2, 2010
 M. Wu, R. C. Miller, and S. L. Garfinkel, “Do security toolbars actually prevent phishing attacks?” in Proc. SIGCHI Conf. Human Factors Comput. Syst., Montreal, QC, Canada, Apr. 2006, pp. 601–610.
 N. Chou et al., “Client-Side Defense Against Web-Based Identity Theft,” Proc. Network and IT Security Symposium, Internet Soc., 2004; http://cryptoanford.edu/SpoofGuard/webspoof.pdf
 “Fighting Phishing with Discriminative Keypoint Features” Kuan-Ta Chen, Chun-Rong Huang, and Chu-Song Chen Institute of Information Science, Chen Columbia University Published by the IEEE Computer Society 1089-7801/09/$25.00 © 2009 IEEE INTERNET COMPUTING
 C.C. Zou, D. Towsley, and W. Gong, “Modeling and Simulation Study of the Propagation and Defense of Internet E-Mail Worms,” IEEE Trans. Dependable and Secure Computing, vol. 4, no. 2, pp. 105- 118, Apr.-June 2007.
 Z. Chen and C. Ji, “Spatial-Temporal Modeling of Malware Propagation in Networks,” IEEE Trans. Neural Networks, vol. 16, no. 5, pp. 1291-1303, Sept. 2005.
 C. Gao, J. Liu, and N. Zhong, “Network Immunization and Virus Propagation in Email Networks: Experimental Evaluation and Analysis,” Knowledge and Information Systems, vol. 27, pp. 253-279, 2011.
 S. Wen, W. Zhou, Y. Wang, W. Zhou, and Y. Xiang, “Locating Defense Positions for Thwarting the Propagation of Topological Worms,” IEEE Comm. Letters, vol. 16, no. 4, pp. 560-563, Apr. 2012.
 J. Xiong, “Act: Attachment Chain Tracing Scheme for Email Virus Detection and Control,” Proc. ACM Workshop Rapid Malcode (WORM ’04), pp. 11-22, 2004.
 IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, VOL. 11, NO. 4, JULY/AUGUST 2014 Modeling and Analysis on the Propagation Dynamics of Modern Email Malware Sheng Wen, Student Member, IEEE, Wei Zhou, Jun Zhang, Member, IEEE.
 International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com “Detection Phishing Emails Using Features Decisive Values” Noor Ghazi M. Jameel Loay E. George Computer Science Institute Assistant Professor Sulaimani Polytechnic University College of Science Kurdistan Region.
 IEEE COMMUNICATIONS SURVEYS & TUTORIALS, VOL. 15, NO. 4, FOURTH QUARTER 2013 A Survey of Phishing Email Filtering Techniques Ammar Almomani, B. B. Gupta, Samer Atawneh, A. Meulenberg, and Eman Almomani .
Phishing Email, legitimate Email, vulnerability, Anti-phishing, SVM, Heuristics, Machine Learning Algorithm.