Research And Design Of Real Time Network Trustworthiness Evaluation Based On Context Awareness

With the rapid development of computing technology in the information age,the scale of the Internet has increased rapidly at an unprecedented rate,and people's daily life has been unable to leave the Internet.However,Internet is a distributed heterogeneous network.The traditional static trust evaluation technology and centralized trusted evaluation technology have been difficult to keep pace with the development of Internet.Therefore,network trustworthiness assessment is in urgent need of a real-time trusted evaluation method for large-scale distributed network,which is used to cope with today's complex network security problems,and to ensure that Internet can provide stable and reliable network services.According to the above problems,in view of the characters of the diversity of network node and the high cost of communication,this paper design a trusted evaluation method based on context.The main content of this paper is as follows:(1)This paper presents a real-time and trusted network evaluation method based on context.To a certain extent this method improves the accuracy of trusted evaluation,which uses the historical behavior information and current state information in a trusted evaluation and which combines behavior situation information and primary situational information based on network.(2)This paper presents a calculation method of trust value based on recurrent neural networks and time series,which improves the integrity of situational information in trusted computing by using recurrent neural networks have a good memory for historical information.(3)This paper presents a selection framework about nodes in trusted evaluation management based on cloud model.This framework improves the stability of trusted evaluation,which combines cloud model and time situation information.Aiming at the above trust evaluation method,a simulation experiment is designed,and the experimental results show that the method can significantly improve the accuracy and stability of the credibility evaluation.