International Scientific Journal of Engineering and Management

An International Scholarly || Multidisciplinary || Open Access || Indexing in all major Database & Metadata
ISSN: 2583-6129

Impact Factor: 6.674

PHISHING WEBSITE DETECTION

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  • Create Date 14 May 2023
  • Last Updated 14 May 2023

PHISHING WEBSITE DETECTION

Akanksha S Gatty, Poorvi M Rao, R Devika, Sanjana Arun Prabhas,

Information Science and Engineering Department, AJ Institute of Engineering and Technology

 

Abstract- Phishing is the technique of extracting user credentials and sensitive data from users by masquerading as a genuine website. In phishing, the user is provided with a mirror website that is identical to the legitimate one but with malicious code to extract and send user credentials to phishers. Blacklist, heuristic, visual scan and machine learning are a few anti-phishing strategies. Our proposed system does the task of extracting the various features from the URL, to check whether the site is a fraud site or not. Machine learning is a reliable method to recognize phishing.

 


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