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- W2397635110 abstract "Phishing is an act of cracking by single person or group of persons to stolen the personal confidential information such as credit card detail, bank account detail, passwords etc., from unknown sufferer for illegal activities. In this paper we have implemented the text classifier using Bayesian approach for phishing detection. Text classifier works on textual content for measuring the similarity between the real web page and untrustworthy web page. Stemming is used for simplicity of our model. For generating threshold we used probabilistic approach with large data set of homepage URLs. The experimental result gives phishing pages detection ratio is 98.87% also for FAR is nearly equal to zero." @default.
- W2397635110 created "2016-06-24" @default.
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- W2397635110 date "2015-09-02" @default.
- W2397635110 modified "2023-09-25" @default.
- W2397635110 title "Anti-Phishing based on Text Classification using Bayesian Approach" @default.
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