Users' behavioral prediction for phishing detection
Journal
23rd International Conference on World Wide Web
Pages
337-338
ISBN
9781450327459
Date Issued
2014
Author(s)
Abstract
This study explores the users' web browsing behaviors that confront phishing situations for context-aware phishing detection. We extract discriminative features of each clicked URL, i.e., domain name, bag-of-words, generic Top-Level Domains, IP address, and port number, to develop a linear chain CRF model for users' behavioral prediction. Large-scale experiments show that our method achieves promising performance for predicting the phishing threats of users' next accesses. Error analysis indicates that our model results in a favorably low false positive rate. In practice, our solution is complementary to the existing anti-phishing techniques for cost-effectively blocking phishing threats from users' behavioral perspectives. ? Copyright 2014 by the International World Wide Web Conferences Steering Committee.
Subjects
Behavioral analysis
Category prediction
Context-aware detection
Other Subjects
Forecasting; Information retrieval; World Wide Web; Behavioral analysis; Browsing behavior; Context-Aware; Discriminative features; False positive rates; Large scale experiments; Phishing detections; Top level domains; Computer crime
Type
conference paper