Dr. Phish: Phishing Website Detector

+91-7667918914 iarjset@gmail.com 0 Items International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal ISSN Online 2393-8021 ISSN Print 2394-1588 Since 2014 Home About About IARJSET Aims and Scope Editorial Board Editorial Policies Publication Ethics Publication Policies Indexing and Abstracting Citation Index License Information Authors How can I publish my paper? Instructions to Authors Benefits to Authors Why Publish in IARJSET Call for Papers Check my Paper status Publication Fee Details Publication Fee Mode FAQs Author Testimonials Reviewers Topics Peer Review Current Issue & Archives Indexing FAQ’s Contact Select Page Dr. Phish: Phishing Website Detector Harish Kumar, Anshal Prasad, Ninad Rane, Nilay Tamane, Dr. Anjali Yeole

Abstract: Phishing is an attack on gullible people by making them disclose their personal and unique information. It is a cyber-crime where false sites attract exploited people to give delicate data. This paper describes the various techniques for detecting phishing websites by analyzing different attributes of URLs with the help of ML techniques.This experimentation discusses the techniques used for detecting phishing websites by extracting their features like URL length, port, HTTPS token and many more. We have used data mining techniques for the extraction of the features of an URL in order to get a clear image of URL's structure that spread phishing. To protect the end users from entering these types of phished websites, we can try to predict whether an URL is phished or not. A challenge in this field is that attackers are constantly making new strategies to tackle our defensive methods. To continuously update our system in this domain, we need ML algorithms that adapt to new instances and features of phishing URLs. Keywords - phishing , anti-phishing , machine learning , cyber-crime , cyber-attack Downloads: | DOI: 10.17148/IARJSET.2021.8831 How to Cite: [1] Harish Kumar, Anshal Prasad, Ninad Rane, Nilay Tamane, Dr. Anjali Yeole, "Dr. Phish: Phishing Website Detector," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: IARJSET.2021.8831 Copy Citation Call for Papers Rapid Publication 24/7 April 2026 Submission: eMail paper now Notification: Immediate Publication: Immediately with eCertificates Frequency: Monthly Downloads Paper Format Copyright Form   Submit to iarjset@gmail.com or editor@iarjset.com   Submit My Paper Author CenterHow can I publish my paper? Publication Fee Why Publish in IARJSET Benefits to Authors Guidelines to Authors FAQs (Frequently Asked Questions) Author Testimonials IARJSET ManagementAims and Scope Call for Papers Editorial Board DOI and Crossref Publication Ethics Editorial Policies Publication Policies Subscription / Librarian Conference Special Issue Info ArchivesCurrent Issue & Archives Conference Special Issue Copyright © 2026 IARJSET This work is licensed under a Creative Commons Attribution 4.0 International License. Open chat