Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

A Proposal on Phishing URL Classification for Web Security

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2019
Sonam Saxena, Amit Shrivastava, Vijay Birchha

Sonam Saxena, Amit Shrivastava and Vijay Birchha. A Proposal on Phishing URL Classification for Web Security. International Journal of Computer Applications 178(39):47-49, August 2019. BibTeX

	author = {Sonam Saxena and Amit Shrivastava and Vijay Birchha},
	title = {A Proposal on Phishing URL Classification for Web Security},
	journal = {International Journal of Computer Applications},
	issue_date = {August 2019},
	volume = {178},
	number = {39},
	month = {Aug},
	year = {2019},
	issn = {0975-8887},
	pages = {47-49},
	numpages = {3},
	url = {},
	doi = {10.5120/ijca2019919282},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Data mining and machine learning is one of the most essential tools in new generation technology. That is used in a number of applications i.e. security, banking and decision making. In this paper, data mining application of web data security is described in details. In this context the domain of phishing URL detection and classification is key aim of the proposed work. This paper includes the different aspects of phishing and recently made contributions for accurately classification of phishing URLs. In addition of that a data mining based model is also proposed that is help to classify the phishing URLs more accurately. Finally the paper provides the future extension of the work.


  1. B. B. Gupta, Nalin A.G. Arachchilage, Konstantinos E. Psannis, “Defending against Phishing Attacks: Taxonomy of Methods, Current Issues and Future Directions”,
  2. G.Parthasarathy, D.C.Tomar, K. Christina Praisy, “AN ENHANCEMENT OF ASSOCIATION CLASSIFICATION ALGORITHM FOR IDENTIFYING PHISHING WEBSITES”, Indian Journal of Computer Science and Engineering (IJCSE) Vol. 7 No. 4 Aug-Sep 2016
  3. R. Sathya, Annamma Abraham, “Comparison of Supervised and Unsupervised Learning Algorithms for Pattern Classification”, International Journal of Advanced Research in Artificial Intelligence, Vol. 2, No. 2, 2013
  4. Patrick Dave P. Woogue, Gabriel Andrew A. Pineda, and Christian V. Maderazo, “Automatic Web Page Categorization Using Machine Learning and Educational-Based Corpus”, International Journal of Computer Theory and Engineering, Vol. 9, No. 6, December 2017
  5. Zheng Dong, Apu Kapadia, Jim Blythe and L. Jean Camp, “Beyond the Lock Icon: Real-time Detection of Phishing Websites Using Public Key Certificates”, 978-1-4799-8909-6/15/$31.00 c 2015 IEEE
  6. Peter F. Likarish, “Early detection of malicious web content with applied machine learning”, PhD (Doctor of Philosophy) thesis, University of Iowa, 2011.
  8. Parth Parekh, Kajal Parmar, Pournima Awate, “Spam URL Detection and Image Spam Filtering using Machine Learning”, International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056, Volume: 05 Issue: 07 | July 2018
  9. Neda Abdelhamid, Fadi Thabtah, Hussein Abdel-jaber, “Phishing Detection: A Recent Intelligent Machine Learning Comparison based on Models Content and Features”, 978-1-5090-6727-5/17/$31.00 ©2017 IEEE
  10. Hemali Sampat, Manisha Saharkar, Ajay Pandey, Hezal Lopes, “Detection of Phishing Website Using Machine Learning”, International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056, Volume: 05 Issue: 03 | Mar-2018
  11. Anna L. Buczak, and Erhan Guven, “A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection”, IEEE COMMUNICATIONS SURVEYS & TUTORIALS, VOL. 18, NO. 2, SECOND QUARTER 2016
  12. Mahmood Moghimi, Ali Yazdian Varjani, “New rule-based phishing detection method”, Expert Systems With Applications 53 (2016) 231–242


Data mining, machine learning, classification, Phishing URL, web security.