International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Classification Model for Phishing e-mails with a Datamining Approach

Author : Sharmila S P ¹ Balaji Rao Katika ²

Date of Publication :20th April 2021

Abstract: In the field of computer security, phishing attacks are one of the trending cyber-attacks. Phishing is an online criminal act that occurs when a malicious webpage impersonates as legitimate webpage so as to acquire sensitive information such as username, password, bank details by masquerading as a trustworthy entity. Attackers create a replica of an existing web page to fool users (e.g. e-mails, instant messages etc.). Phishing attack continues to pose a serious risk for web users and annoying threat within the field of electronic commerce. The increasing number of phishing websites has become a great challenge in e-business in general and in electronic banking also. The attacker makes a fake webpage by copying or making a little change in the legitimate page, so that an internet user will not able to differentiate between phishing and legitimate webpages. So, it is important to develop techniques which help in reducing these attacks. The theme of our project is to reduce the attacks by identifying them in the first place and avoid people to fall into such kind of traps.

Reference :

1. Federal Trade Commission, et al. Consumer Sentinel Network Data Book for January–December 2015, 2016.
2. L. OpenDNS, PhishTank, 2016, https://www.phishtank.com/index.php.
3. APWG, Phishing activity trends report, 3rd Quarters 2020, Report, APWG. Activity July-September 2020 Published 24, November 2020. https://docs.apwg.org/reports/apwg_trends_report_q3 _2020.pdf
4. A. Almomani, T.-C. Wan, A. Manasrah, A. Altaher, M. Baklizi, S. Ramadass, “An enhanced online phishing e-mail detection framework based on evolving connectionist system”, International Journal of Innovative Computing, Information and Control (IJICIC) 9 (2013) 169–175.
5. Sami Smadi, Nauman Aslam, Li Zhang “Detection of online phishing email using dynamic evolving neural network based on reinforcement learning” Department of Computer and Information Science, Northumbria University, UK
6. A. Vishwanath, T. Herath, R. Chen, J. Wang, H.R. Rao, “Why do people get phished? Testing individual differences in phishing vulnerability within an integrated, information processing model”, Decision Support Systems 51 (2011)576–586.
7. C.L. Tan, K.L. Chiew, K. Wong, “PhishWHO: Phishing webpage detection via identity keywords extraction and target domain name finder”, Decision Support Systems 88 (2016) 18–27.
8. K. Krombholz, H. Hobel, M. Huber, E. Weippl, “Advanced social engineering attacks”, Journal of Information Security and Applications 22 (2015) 113–122.
9. D.D. Caputo, S.L. Pfleeger, J.D. Freeman, M.E. Johnson, “Going spear phishing: exploring embedded training and awareness”, IEEE Security & Privacy 12 (2014) 28–38.
10. Afroz and Greenstadt (2006). “A machine learning Approach to phishing Detection and defence”.
11. M. Chandrasekaran, et al., “Phishing email detection based on structural properties”, in New York State Cyber Security Conference (NYS) , Albany, NY ,” 2006 [11] P. R. a. D. L. Ganger, “Gone phishing: Evaluating anti-phishing tools for windows. Technical report,” September 2006.
12. M. Bazarganigilani, “Phishing E-Mail Detection Using Ontology Concept and Nave Bayes Algorithm,” International Journal of Research and Reviews in Computer Science, vol. 2, no.2, 2011.
13. Elsevier B.V(2015) “An ideal approach for detection and prevention of phishing attack”, 4th international conference on advances in computing, communication and control.
14. M. Chandrasekaran, et al. (2006), “ Phishing email detection based on structural properties”, in New York State Cyber Security Conference (NYS), Albany, NY,”.
15. A. Bergholt, et al., “Improved phishing detection using model-based features,” in Proc. Conference on Email and Anti-Spam (CEAS). Mountain View Conf, CA, aug 2008.
16. L. Ma, et al., “Detecting phishing emails using hybrid features,” IEEE Conf, 2009, pp. 493-497.
17. Ahmed Aleroud, Lina Zhou, “Phishing environments, techniques, and countermeasures: a survey”
18. L. Joy Singh, “A Survey on Phishing and AntiPhishing Techniques”, NIELIT IMPHAL IJCST Mar-Apr 2018