Spam and Non-Spam URL Detection using Machine Learning Approach
Ritu Raj, Sandeep Singh Kang · 2022 3rd International Conference for Emerging Technology (INCET) · 2022
In the modern world, where everyone is connected with internet, a threat has always surrounded every internet user which steals user credentials by various means; this threat is known as Phishing. The attacker acts as a trustworthy agent and steals victim’s credentials or personal details. This information is then used for illegal purpose which may result in identity theft or financial loss. This project provides a better understanding on how phishing attacks are carried out by attackers and how these attacks are detected by websites that uses various detection methods. A tool is designed using machine learning and deep neural net which classify Uniform Resource Locator (URLs) as phishing or legitimate URL. Dataset is collected from various resources that contain phishing and legitimate URLs of websites and then these datasets are provided to the neural net for supervised training. Various classification algorithms are, then, applied on these datasets and then accuracy of these algorithms is predicted.