3 comp sci ijcse conditional naive bayes pushpalatha aish

K. Venkateswara Reddy & N. Pushpalatha

N. Pushpa Latha working as a Assistant professor in Marri Laxman Reddy Institute of Technology and Management, Hyderabad. She has 6+ years teaching experience and good knowledge in computer subjects. She completed master degree in co mputer science and engineering dept. fro m University College of Engg, JNTU Campus, Kakinada. Presently pursuing Ph. D fro m JNTU, Hyderabad.

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3 comp sci ijcse conditional naive bayes pushpalatha aish

Published on May 5, 2014

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An intruder mas querades as the legitimate us er to obtain authorization on legitimate us ers account. Thes e Mas querades has to be detected as early as poss ible , effic iently to reduce the malic ious work done on that account. This paper propos es a novel approach for detecting the mas querades , which is not only effic ient and als o accurate than the earlier methods . Here we concentrate on the deviations of us er pro file with the trained profile, wh ich are diffe rent bas e on duration of deviation for legitimate us er and mas querades . Us ing this concept we extended the work done by Roy A Maxion [1] to device a Conditional Naïve Bayes method. Experiments on a s tandard datas ets demons trate that this Conditional Naïve Bayes clas s ifier beats the previous best performing detector and reduces the mis s ing -alarm rate and increas es the hit rate.

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