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Trusted and reliable wireless sensor networks (WSNs) rely on the accurate and rapid detection of anomalies. However, the security model in wired networks is not suited for WSNs because of their energy constraints. In this paper, a traffic prediction model based on gene expression programming (GEP-ADS) is proposed, to predict the time series of normal traffic. Then we present a lightweight anomaly...
In order to decrease the traffic in the wireless sensor networks, a gene expression programming based temporal data aggregation technique (GEP-WSNDA) is presented. Two matching predictors with the same GEP-WSNDA models are deployed at the server and the node respectively, which predict the next immediate sampling value simultaneously. The sampling value and new model are sent to the server only when...
Under the application background of network security evaluation research, this paper proposes a method of situation prediction based on particle swarm optimization (PSO) for optimizing BP neural network (BPNN). It uses PSO to reach global optimization of BP network's weight value and threshold value, and then by means of the optimized BP network builds a prediction model to predict the future network...
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