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Phishing-Classification

Abstract:

With the increase in number of users and user’s personal data there has also been a rapid increase in online scams.Usually, it is difficult to classify a website as malicious because of changing syntax of the URLs and because of use of redirection using shortened URLs. This problem is tackled using Machine Learning techniques to classify a website as either legitimate or spam.

Dataset :

The dataset considered for this project is taken from Kaggle website under the topic of phishing website dataset. The dataset consists of total 12 columns including the target variable. Some of sample data from the given dataset is shown below

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