Enhancing Security on Social Networks with IoT-based Blockchain Hierarchical Structures with Markov Chain

With the development of IoT, the devices connected to this platform, can exchange data and share their data in social networks. Although this possibility provides advantage, but is has some security challenges like preserving privacy, confidentiality, accessibility, and data integrity in the social networks. In the existing studies, a type of encoding has been used for preserving security. In this paper for improving the security, we introduce a Markov process for describing a security attack model based on Markov transmission matrix. By applying the Markov transmission in blockchain infrastructure we will enhancing security in blockchain‐based social networks. A security threat is a random process. Therefore, we can modelled it as a Markov chain. First the proposed method is compared to SHA1, and results show that the complexity is improved 215% and 240% in terms of hash length, and internal state size, respectively. In this study, nine hash functions, including SHA, four families of SHA2, and four families of SHA3, including SHA3-512, SHA3-384, SHA3-256, and SHA3-224 are simulated ten times. The results indicate a security improvement of 206.59% of SHA3-512 compared to other functions.