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MOBILE SECURITY USING SUPERVISED LEARNING
Authors: PUNDIR P.R., GOMASE V.S
Number of views: 564
Wireless networks in small or large coverage are increasingly popular as they promise the expected convergence of voice and data services while providing mobility to users. Combining with current wireless communications infrastructure, wireless computing infrastructure and mobile middleware, mobile commerce provides consumers with faster and personalized services and is becoming one of the most important wireless applications. Unless the transmission, storing and processing of information is secure, neither customers nor service providers will trust mobile commerce systems. From a technical point of view, mobile commerce over wireless networks is inherently insecure compared to electronic commerce over wired networks. A number of machine learning algorithms has to be redesigned to address growing concerns with security due to unlimited explosion of new information through internet cloud and other media. In this paper, we have presented the applications of association rules, privacy decision-tree model, Artificial Neural Network, Support Vector Machine, and HMM. Mobile security is a crucial issue for mobile commerce.