Phishing Detection Using Significant Feature Selection
Debkalpa Goswami, Manali Shukla, Anshu Chaturvedi · 2020
Growth of cyber attacks is rapidly increasing in the entire world. To provide prevention from these attacks is a great challenge for the experts. Intruders are keep on adapting new methods and techniques to carry out their malicious goals. Phishing plays a dominant role in the field of web attacks and it has been used as a weapon by the attackers. In this paper we have given two algorithmic approaches to the problem of Phishing identification with reduced number of attributes. It makes this approach simple yet efficient. The first algorithm assigns weight to all attributes with respect to uniform resource locators. We have employed various analysis mechanism to identify significant role of selected attributes for the purpose of Phishing identification. The second approach takes former's output as input and classifies the uniform resource locators labeling as phishing or non phishing. The experimental work verifies that the approach for phishing detection proposed in this paper can attain a high accuracy in comparison to existing algorithms.