Scalable Detection and Isolation of Phishing
نویسندگان
چکیده
This paper presents a proposal for scalable detection and isolation of phishing. The main ideas are to move the protection from end users towards the network provider and to employ the novel bad neighbourhood concept, in order to detect and isolate both phishing e-mail senders and phishing web servers. In addition, we propose to develop a self-management architecture that enables ISPs to protect their users against phishing attacks, and explain how this architecture could be evaluated. This proposal is the result of half a year of research work at the University of Twente (UT), and it is aimed at a Ph.D. thesis in 2012.
منابع مشابه
Phishing 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 کاملA Novel Architecture for Detecting Phishing Webpages using Cost-based Feature Selection
Phishing is one of the luring techniques used to exploit personal information. A phishing webpage detection system (PWDS) extracts features to determine whether it is a phishing webpage or not. Selecting appropriate features improves the performance of PWDS. Performance criteria are detection accuracy and system response time. The major time consumed by PWDS arises from feature extraction that ...
متن کاملCollaborative Detection of Fast Flux Phishing Domains
Phishing is a significant security threat to users of Internet services. Nowadays, phishing has become more resilient to detection and trace-back with the invention of Fast Flux (FF) service networks. We propose two approaches to correlate evidence from multiple DNS servers and multiple suspect FF domains. Real-world experiments show that our correlation approaches speed-up FF domain detection,...
متن کاملDetecting 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 کاملFeature-based Malicious URL and Attack Type Detection Using Multi-class Classification
Nowadays, malicious URLs are the common threat to the businesses, social networks, net-banking etc. Existing approaches have focused on binary detection i.e. either the URL is malicious or benign. Very few literature is found which focused on the detection of malicious URLs and their attack types. Hence, it becomes necessary to know the attack type and adopt an effective countermeasure. This pa...
متن کامل