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Adaptive Classifier and Associative Algorithms for Phishing Detection

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Executive Summary

Phishing serves as a social engineering crime generally known as impersonating a trusted third party to gain access to private data. Data Mining (DM) Techniques might be a very useful methodology for identifying and detecting phishtank phishing websites. Using this proposed system, the authors present a novel approach to overcome the challenge and complexity in detecting and predicting offline phishing data. They proposed an intelligent effective model that really based on using improved classification like improvedC4 5, PRISM,PART and association Mining algorithms MCAR. This strategy uses different classification algorithm and techniques to extract the phishing training dataset to sort out their legitimacy.

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