Biblio

To understand the future trend of network security, the field of network security began to introduce the concept of NSSA(Network Security Situation Awareness). This paper implements the situation assessment model by using game theory algorithms to calculate the situation value of attack and defense behavior. After analyzing the ant colony algorithm and the RBF neural network, the defects of the RBF neural network are improved through the advantages of the ant colony algorithm, and the situation prediction model based on the ant colony-RBF neural network is realized. Finally, the model was verified experimentally.

In this paper, we propose a power allocation scheme in order to improve both secure and reliable performance in the wireless two-hop threshold-selection decode-and-forward (DF) relaying networks, which is so crucial to set a threshold value related the signal-to-noise ratio (SNR) of the source signal at relay nodes for perfect decoding. We adapt the maximal-ratio combining (MRC) receiving SNR from the direct and relaying paths both at the destination and at the eavesdropper. Particularly worth mentioning is that the closed expression form of outage probability and intercept probability is driven, which can quantify the security and reliability, respectively. We also make endeavors to utilize a metric to tradeoff the security and the reliability (SRT) and find out the relevance between them in the balanced case. But beyond that, in the pursuit of tradeoff performance, power allocation tends to depend on the threshold value. In other words, it provides a new method optimizing total power to the source and the relay by the threshold value. The results are obtained from analysis, confirmed by simulation, and predicted by artificial neural networks (ANNs), which is trained with back propagation (BP) algorithm, and thus the feasibility of the proposed method is verified.