Data Mining for Information Security: An Experimental Approach
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Information security is an important issue for any organization or individual to protect data and information from unauthorized access. Valuable data and information are kept in the system connected through the computer network and are needed to secure against the intruders. Data Mining techniques provides solution to overcome the above mentioned problem. This book explores various data mining techniques like C-4.5, CART, CHAID, QUEST, Random Forest etc. with special reference to feature selection and used to develop models. An attempt has been made to develop ensemble model also, models were ...
Information security is an important issue for any organization or individual to protect data and information from unauthorized access. Valuable data and information are kept in the system connected through the computer network and are needed to secure against the intruders. Data Mining techniques provides solution to overcome the above mentioned problem. This book explores various data mining techniques like C-4.5, CART, CHAID, QUEST, Random Forest etc. with special reference to feature selection and used to develop models. An attempt has been made to develop ensemble model also, models were tested with many benchmark data sets like spam e-mail, KDD99, NSL-KDD and verified with many classification measures. These models as classifier are required to be deployed in the network or individual computer which will classify unwanted data and will alarm to the users for taking appropriate action. A brief experimental work has been carried out with above benchmark data sets using data mining software like WEKA and Clementine.
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