Efficient Detection of Legitimate and Malicious URLs using ID3 Algorithm

Abstract

Malicious websites are one of the serious threat over the internet. Ever since the inception of the internet, there has been a rise in malicious content over the web such has terrorism, financial fraud, phishing and hacking that targets user’s personal information. Till date, the various systems have been used for the detection of a malicious website based on text and content of the websites. This method has some disadvantages and the numbers of victims have therefore continued to increase. Here we developed a system which helps the user to identify whether the website is malicious or not. Our system identifies whether the site is malicious or not through URL. The proposed system is fast and more accurate compared to current system. The classifier is trained with datasets of 1000 malicious sites and 1000 legitimate site URLs. Trained classifier is used for detection of malicious URLs.