A Classification Model for Detection of Chinese Phishing E-Business Websites
نویسندگان
چکیده
There has been an increasing number of fake e-Business websites created and used, which have resulted in rising financial loss for online consumers and businesses. Therefore, developing effective approaches to detecting phishing websites is essential to mitigating the possibility of being victimized by those sites and minimizing financial loss and risks. In this research, we propose a novel classification model for automatically detecting Chinese phishing e-Business websites. By extending previous research and incorporating unique characteristics of Chinese e-Business websites, our model consists of feature vectors of both the URL and content of a Website. We have trained and evaluated the proposed model with roughly 900 Chinese e-Business websites using four different classification algorithms. Results show that among those four algorithms, the Sequential Minimal Optimization (SMO) algorithm performs the best. To examine the impact of individual features in the model on detection accuracy, we further conducted a sensitivity analysis to identify the most influential features, which helps make the classification model more parsimonious. The findings of this research provide several research and practical insights into the development of anti-phishing solutions.
منابع مشابه
Detecting Fake Websites Using Swarm Intelligence Mechanism in Human Learning
The internet and its various services have made users to easily communicate with each other. Internet benefits including online business and e-commerce. E-commerce has boosted online sales and online auction types. Despite their many uses and benefits, the internet and their services have various challenges, such as information theft, which challenges the use of these services. Information thef...
متن کاملPhishing website detection using weighted feature line embedding
The aim of phishing is tracing the users' s private information without their permission by designing a new website which mimics the trusted website. The specialists of information technology do not agree on a unique definition for the discriminative features that characterizes the phishing websites. Therefore, the number of reliable training samples in phishing detection problems is limited. M...
متن کاملIntelligent Detection System for e-banking Phishing websites using Fuzzy Data Mining
Detecting and identifying e-banking Phishing websites is really a complex and dynamic problem involving many factors and criteria. Because of the subjective considerations and the ambiguities involved in the detection, Fuzzy Data Mining Techniques can be an effective tool in assessing and identifying e-banking phishing websites since it offers a more natural way of dealing with quality factors ...
متن کاملPhishing Detection Plug-In Toolbar Using Intelligent Fuzzy-Classification Mining Techniques
Detecting phishing website is a complex task which requires significant expert knowledge and experience. So far, various solutions have been proposed and developed to address these problems. Most of these approaches are not able to make a decision dynamically on whether the site is in fact phished, giving rise to a large number of false positives. In this paper we have investigated and develope...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013