An Approach to URL Filtering in SDN

Phishing is considered as a form of the Internet crime. To detect a phishing website, human experts compare the claimed identity of the website with the features of the website along with its content. Every website URL has its own lexical features like length, domain names, etc. The phishing websites may appear to perform the same activities of another website but the content of the two websites will be different. In traditional networks, a proxy server handles the URL requests and determines whether an URL is malicious or not. In this paper, URL filtration is incorporated into an SDN framework as a security application. The proposed system uses deep packet inspection and machine learning techniques at the controller and the rule installation in the switches for efficient URL phishing detection. The phishing system analyzes the lexical and content-based features of the URLs. Based on the categorization, the rules are formed and installed in the switches. The performance of the system is evaluated based on the response time and accuracy in the detection of phishing URLs using a simulation framework.

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