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One of the important issues faced in the domain of target classification in wireless sensor networks is the restricted lifetime of individual sensors, caused by limited battery capacity. Although the base station usually has sufficient energy supply and computational power, it is often deemed to be the object of enemy invading hostile terrain. Hence, minimizing energy consumption of sensors while maintaining a given classification accuracy is a key problem in this research area, especially for sensitive data applications. This paper proposes a rule based feature selection approach rather than all-features approach that aims at increasing the energy efficiency of the system without losing much classification accuracy. In experiments, the feasibility and effectiveness of our approach are demonstrated empirically.

A Rule Based Feature Selection Approach for Target Classification in Wireless Sensor Networks with Sensitive Data Applications