Abstract
AbstractWith the growth of the Internet, network security issues have become increasingly complex, and the importance of node interaction security is also gradually becoming prominent. At present, research on network security protection mainly starts from the overall perspective, and some studies also start from the interaction between nodes. However, the trust management mechanisms in these studies do not have a predictive function. Therefore, to predict trust levels and protect network security, this paper innovatively proposes a trust management system for network security protection based on the improved hidden Markov model. The research divides the trust level of inter-node interactions by calculating the threat level of inter-node interactions and predicts the trust level of inter-node interactions through an optimized hidden Markov model. In addition, the study designs an estimation of the types of interactive threats between nodes based on alarm data. The research results show that when inactive interaction tuples are not excluded, the average prediction accuracy of the combined model is 95.5%. In response time, the maximum values of the active and passive cluster management pages are 38 ms and 33 ms, respectively, while the minimum values are 16 ms and 14 ms, with an average of 26.2 ms and 24 ms, respectively. The trust management system designed by the research institute has good performance and can provide systematic support for network security protection, which has good practical significance.
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Signal Processing
Reference17 articles.
1. Z. Chen, Research on internet security situation awareness prediction technology based on improved RBF neural network algorithm. J Comput Cogn Eng. 1(3), 103–108 (2022)
2. R. Islambouli, Z. Sweidan, A. Mourad, C. Abou-Rjeily, Towards trust-aware IoT hashing offloading in mobile edge computing., International Wireless Communications and Mobile Computing (IWCMC). IEEE. 2020, 2216–2221 (2020)
3. S. Thabit, Y. Lianshan, Y. Tao, A.B. Abdullah, Trust management and data protection for online social networks. IET Commun 16(12), 1355–1368 (2022)
4. E. Alemneh, S.M. Senouci, P. Brunet, T. Tegegne, A two-way trust management system for fog computing. Futur Gener Comput Syst. 106(6), 206–220 (2020)
5. H. Xia, W. Yang, Security access solution of cloud services for trusted mobile terminals based on trust zone. Int J Netw Secur. 22(2), 201–211 (2020)
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