Biblio

Multipath fading as well as shadowing is liable for the leakage of confidential information from the wireless channels. In this paper a solution to this information leakage is proposed, where a source transmits signal through a α-μ/α-μ composite fading channel considering an eavesdropper is present in the system. Secrecy enhancement is investigated with the help of two fading parameters α and μ. To mitigate the impacts of shadowing a α-μ distribution is considered whose mean is another α-μ distribution which helps to moderate the effects multipath fading. The mathematical expressions of some secrecy matrices such as the probability of non-zero secrecy capacity and the secure outage probability are obtained in closed-form to analyze security of the wireless channel in light of the channel parameters. Finally, Monte-Carlo simulations are provided to justify the correctness of the derived expressions.

Network situation value is an important index to measure network security. Establishing an effective network situation prediction model can prevent the occurrence of network security incidents, and plays an important role in network security protection. Through the understanding and analysis of the network security situation, we can see that there are many factors affecting the network security situation, and the relationship between these factors is complex., it is difficult to establish more accurate mathematical expressions to describe the network situation. Therefore, this paper uses the grey neural network as the prediction model, but because the convergence speed of the grey neural network is very fast, the network is easy to fall into local optimum, and the parameters can not be further modified, so the Multi-Swarm Chaotic Particle Optimization (MSCPO)is used to optimize the key parameters of the grey neural network. By establishing the nonlinear mapping relationship between the influencing factors and the network security situation, the network situation can be predicted and protected.