DETAILED STUDIES ON PHISHING WEBPAGE DETECTION IN DATA MINING
Sachin Sharma
Dept Computer Science and Engg, Research Scholar, KITE,Jaipur , IN
R L Yadav
Dept Computer Science and Engg, Research Scholar, KITE,Jaipur , IN
Keywords: Data Mining, Phishing Detection, Phishing Attack, Phishing Techniques, Classification.
Abstract
As an application of data mining, businesses can learn more about their customers and develop more effective strategies related to various business functions and in turn leverage resources in a more optimal and insightful manner. This helps businesses be closer to their objective and make better decisions. Data mining involves effective data collection and warehousing as well as computer processing. For segmenting the data and evaluating the probability of future events, data mining uses sophisticated mathematical algorithms. Data mining is also known as Knowledge Discovery in Data (KDD). Data mining technique, one of the classifications of technical approach, has shown promising results in detection of phishing websites. As compared to non-technical approaches, data mining techniques can generate classification models which can make prediction on phishing websites in real-time. Phishing is a form of fraud in which the attacker tries to learn sensitive information such as login credentials or account information by sending. This paper studied about phishing detection and prediction using various efficient algorithms. Classification of phishing is defined in this study and phishing techniques as well.
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