Block chain espoused adaptive multi-scale dual attention network with quaternion fractional order meixner moments encryption for cyber security in wireless communication network.

Autonomous driving like subsequent generation cyber-physical system (CPS) with present improvement of wireless communication network, here is a substantial necessity of big data analyzes along greater accurateness and lower delay. Nevertheless, obtainable researches fail to discourse few challenges like adversarial attacks, centralized control, safety and secrecy. For overcome these issues, Blockchain espoused Adaptive multi-scale dual attention network with Quaternion fractional order Meixner moments for Cyber security in Wireless Communication Network (BC-CS-AMSDAN-QFOMM-WCN) is proposed in this manuscript. First, Adaptive multi-scale dual attention network (AMSDAN) approach is presented at the edge layer and mitigate the challenges in the cloud layer. The AMSDAN is built on a block chain environment to alleviate the triple main defies that is encryption, decryption, Mining and Generation of Block. In Encryption phase, every node in a wireless communication network is allotted a public and private key with the help of Quaternion fractional order Meixner moments (QFOMM). In Decryption phase, the digital signature is decrypted into messages through sender's public key. Mining and Generation of Block, a green proof of work mechanism is used to upgrading safety of transacted data. The proposed approach are implemented in Ethereum and Solidity programming language also this efficacy is evaluated through particular performances matrices, such as response time, CPU time, block creation time, delay, sensitivity, throughput, energy efficiency, computational cost, and accuracy. Then the performance of the proposed BC-CS-AMSDAN-QFOMM-WCN method provides 23.31%, 11.03%, 27.89% higher throughput and 36.51%, 13.09%, 22.24% minimum delay compared with existing method like Blockchain Based Privacy Preserving Framework for Emerging 6G Wireless Communications (BC-CS-B-RAN-WCN), Blockchain and Machine Learning for Wireless Communications and Networking Systems (BC-CS-DAG-ML-WCN) and Blockchain-Based Spectrum Sharing Transactions for Multi-Operators Wireless Communication Networks (BC-CS-SS-TSS-WCN) respectively. [ABSTRACT FROM AUTHOR]