Published Paper Details:

The likelihood and severity of network information insecurity are now rising quickly. The methods mostly used by hackers today are to attack end-to-end technology and exploit human vulnerabilities. These techniques include social engineering, phishing, pharming, etc. One of the steps in conducting these attacks is to deceive users with Phishing Uniform Resource Locators (URLs). As results, Phishing URL detection is of great interest nowadays. There have been several scientific studies showing a number of methods to detect Phishing URLs based on machine learning. In this project propose a Phishing URL detection method using machine learning techniques based on our proposed URL behaviours and attributes. Moreover, bigdata technology is also exploited to improve the capability of detection Phishing URLs based on abnormal behaviours. To put it briefly, the proposed detection method is made up of big data technologies, a machine learning algorithm, and a new collection of URL properties and behaviours. The experimental results show that the proposed URL attributes and behaviour can help improve the ability to detect Phishing URL significantly. This is suggested that the proposed system may be considered as an optimized and friendly used solution for Phishing URL detection.