Hybrid features-based prediction for novel phish websites

Phishers frequently craft novel deceptions on their websites and circumvent existing anti-phishing techniques for insecure intrusions,users’ digital identity theft,and then illegal profits. this raises the needs to incorporate new features for detecting novel phish websites and optimizing the existing anti-phishing techniques. in this light,58 new hybrid features were proposed in this paper and their prediction susceptibilities were evaluated by using feature co-occurrence criterion and a baseline machine learning algorithm. empirical test and analysis showed the significant outcomes of the proposed features on detection performance. as a result,the most influential features are identified,and new insights are offered for further detection improvement. © 2016 penerbit utm press. all rights reserved.