Detection of Phishing Websites Using Machine Learning

Registration ID: IJNRD_209355

Published ID: IJNRD2403190

DOI: Click Here to Get

Sugat Ingle , Prince Gupta , Shreyash Bhole , Kamlesh Janawale , Prof. A.N. Kalal

Extreme Learning Machine (ELM), Support Vector Machine (SVM), Random Forest Algorithm, URL Phishing Websites, Browser add-ons.

The detection of phishing websites and online content yields various indicators. One prevalent form of successful cybercrime involves phishing sites that lure users to deceptive websites mimicking legitimate ones, aiming to illicitly obtain personal and sensitive information. The suggested Extreme Learning Machine (ELM)-based version has proven effective in identifying phishing websites. Internet page types exhibit diverse characteristics, requiring the utilization of a set of web page features for protection against phishing attacks. To counter these threats, a machine learning strategy is implemented. The phishing dataset, including authentic URLs from the database and collected data, undergoes pre-processing. Four groups of URL characteristics—domain-based, address-based, anomalous-based, and HTML or JavaScript features are employed for phishing detection. The analysed data is utilized to extract URL characteristics and generate corresponding attribute values. Machine learning approaches are applied to analyse URLs, establishing threshold and range values for URL properties. The project aims to develop an ELM categorization for various database characteristics and identify potential phishing sites.

Published Paper   E-Certificate

Sugat Ingle, Prince Gupta, Shreyash Bhole, Kamlesh Janawale, & Prof. A.N. Kalal (March-2024). Detection of Phishing Websites Using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(3), b829-b833. https://ijnrd.org/papers/IJNRD2403190.pdf

Volume 9 Issue 3, March-2024

Pages : b829-b833

Paper Reg. ID: IJNRD_209355

Published Paper Id: IJNRD2403190

Downloads: 000121987

Research Area: Engineering

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2403190.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403190

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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