Security Optimization and Data Classification in Wireless Sensor Networks

Large populations of wireless connected nodes, capable of computation, communication and sensing constitute wireless sensor networks (WSNs). Since increasing number of applications have been widely deployed using WSNs, selection of the best type of secure data transmission for WSNs becomes one of the most important issues among other challenges. Besides, there is not any secure sensor network protocols proposed using different encryption algorithms at a time depending on a quality of service (QoS) requirement in the literature. However, there is a need for an alternative that brings the optimum, flexible and efficient solution for secure data transmission. Intelligent optimization algorithms can address this problem. In addition to providing a secure data transmission, efficient data classification is a crucial issue in sensor networks in order to obtain accurate data and reduce the communication overhead. In this paper, previously proposed schemes for secure wireless sensor networks are investigated. Furthermore, an optimization algorithm using genetic algorithms for secure transmission is proposed for WSNs. Besides, different classification algorithms are experimented to find an efficient, fast and accurate sensor data classification algorithm. Experiments are performed for these two type of sensor network issues and the results are compared in terms of time and complexity efficiency. Performance analysis is provided to assess the efficiency of the proposed algorithms.