PHISHNET: Multi-Algorithmic Safety Net for Advanced Phishing URL Detection

PHISHNET:  Multi-Algorithmic Safety Net for Advanced Phishing URL Detection

Mrs Anusha M1, Prince Kumar2, Sadhana Kumari3, Mohd. Arsalan Lari4 , P.Sirisha5

1Assistant Professor, Visvesvaraya Technological University, Computer Science, SJB Institute of Technology,    Bangalore, Karnataka, India

2,3,4,5Students, Visvesvaraya Technological University, Computer Science, SJB Institute of Technology, Bangalore,

Karnataka, India

ABSTRACT

Today's generation heavily relies on web technology for various tasks such as banking and communication. However, this also means that users are exposed to numerous security threats, with phishing being one of the most serious and common attacks. Phishing attacks aim to steal sensitive information from users by impersonating a legitimate entity. Attackers use phishing to obtain victims' credentials such as bank account numbers, passwords, or other private information. The victim may not be aware of the website that is phishing. which impersonates a genuine website. Therefore, this paper proposes a system to identify phishing sites using machine learning algorithms. The system utilizes a classifier that is trained on a comprehensive dataset with enriched features.

Keywords: Phishing URL Detection, Machine Learning, Websites