Advancements in Phishing Detection through Machine Learning : A Comparative Analysis |
Author(s): |
| Sakshi Sharad Shirke , BK Birla College of Arts , Science And Commerce , Mumbai , India |
Keywords: |
| Phishing Detection, Machine Learning, Features, Classifiers, Decision Tree, Random Forest, Xgboost, SVM |
Abstract |
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Phishing is the simplest method for gathering sensitive details or information from the user. Phishers try to seek private data, including passwords, login credentials, bank account details, and many more. ML algorithms have emerged as promising tools for detecting phishing attacks. In this research work, using ML techniques, extraction and analysis of both types of URLs were performed. The main aim was to identify phishing URLs and determine the most effective ML technique by comparing the accuracy rates of each algorithm. This paper presents an in-depth analysis of various ML techniques and their applications in phishing detection. |
Other Details |
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Paper ID: IJSRDV11I80051 Published in: Volume : 11, Issue : 8 Publication Date: 01/11/2023 Page(s): 87-89 |
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