An efficient phishing webpage detector |
| |
Authors: | Mingxing He Shi-Jinn Horng Pingzhi Fan Muhammad Khurram Khan Ray-Shine Run Jui-Lin Lai Rong-Jian Chen Adi Sutanto |
| |
Affiliation: | 1. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, India;2. Department of Computer Science, State University of New York at Albany, NY, USA;1. Effat University, College of Engineering, Jeddah, 21478, Saudi Arabia;2. Federal Institute of Statistics, Sarajevo. 71000, Bosnia and Herzegovina |
| |
Abstract: | Phishing attack is growing significantly each year and is considered as one of the most dangerous threats in the Internet which may cause people to lose confidence in e-commerce. In this paper, we present a heuristic method to determine whether a webpage is a legitimate or a phishing page. This scheme could detect new phishing pages which black list based anti-phishing tools could not. We first convert a web page into 12 features which are well selected based on the existing normal and fishing pages. A training set of web pages including normal and fishing pages are then input for a support vector machine to do training. A testing set is finally fed into the trained model to do the testing. Compared to the existing methods, the experimental results show that the proposed phishing detector can achieve the high accuracy rate with relatively low false positive and low false negative rates. |
| |
Keywords: | |
本文献已被 ScienceDirect 等数据库收录! |
|