Efficient Detection of Phishing Websites Using Multilayer Perceptron

Authors

  • Ammar Jamil Odeh Princess Sumaya University for Technology
  • Ismail Keshta AlMaarefa University
  • Eman Abdelfattah Ramapo College of New Jersey

DOI:

https://doi.org/10.3991/ijim.v14i11.13903

Keywords:

Multilayer Perceptron (MLP), Activation function, Semantic attack, Phishing

Abstract


Phishing is a type of Internet fraud that aims to acquire the credential of users via scamming websites. In this paper, a novel approach is utilized that uses a Neural Network with a multilayer perceptron to detect the scam URL. The proposed system improves the accuracy of the scam detection system as it achieves a high accuracy percentage of 98.5%.

Author Biographies

Ammar Jamil Odeh, Princess Sumaya University for Technology

received his Ph.D. Degree in Computer science and Engineering with a concentration in Computer Security (Steganography) from University of Bridgeport. He received M.S. degree in Computer Science with a concentration in Reverse software Engineering and Computer Security from the University of Jordan, College of King Abdullah II School for Information Technology (KASIT). In 2002, he finished B.Sc. Degree in Computer Science and applications, from the Hashemite University, Prince Al-Hussein Bin Abdullah II for Information Technology. During the Ph.D. period, he worked as Research Assistant, Teaching Assistant, and Instructor. He is currently an assistant professor in computer science at Princess Sumaya University for Technology.

Ismail Keshta, AlMaarefa University

received his B.Sc. and the M.Sc. degrees in computer engineering and his Ph.D. in computer science and engineering from the King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia, in 2009, 2011, and 2016, respectively. He was a lecturer in the Computer Engineering Department of KFUPM from 2012 to 2016. Prior to that, in 2011, he was a lecturer in Princess Nourah bint Abdulrahman University and Imam Muhammad ibn Saud Islamic University, Riyadh, Saudi Arabia. He is currently an assistant professor in the computer science and information systems department of AlMaarefa University, Riyadh, Saudi Arabia. His research interests include software process improvement, modeling, and intelligent systems.

Eman Abdelfattah, Ramapo College of New Jersey

currently works at the School of Theoretical & Applied Science, Ramapo College of New Jersey. Eman does research in Machine Learning, Computer Security and Computer Communications (Networks).

Downloads

Published

2020-07-10

How to Cite

Odeh, A. J., Keshta, I., & Abdelfattah, E. (2020). Efficient Detection of Phishing Websites Using Multilayer Perceptron. International Journal of Interactive Mobile Technologies (iJIM), 14(11), pp. 22–31. https://doi.org/10.3991/ijim.v14i11.13903

Issue

Vol. 14 No. 11 (2020)

Section

Papers

License

The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution Licence (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
By submitting an article the author grants to this journal the non-exclusive right to publish it. The author retains the copyright and the publishing rights for his article without any restrictions.
This journal has been awarded the SPARC Europe Seal for Open Access Journals (What's this?)