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.

像下一代信息物理系统（CPS）这样的自动驾驶，加上目前无线通信网络的完善，迫切需要大数据分析的更高准确性和更低的延迟。然而，现有的研究未能讨论对抗性攻击、集中控制、安全性和保密性等挑战。为了克服这些问题，本手稿提出了区块链采用具有四元数分数阶 Meixner 矩的自适应多尺度双重注意网络，用于无线通信网络中的网络安全（BC-CS-AMSDAN-QFOMM-WCN ） 。首先，在边缘层提出自适应多尺度双重注意网络（AMSDAN）方法，并缓解云层的挑战。AMSDAN建立在区块链环境上，以缓解加密、解密、挖掘和生成区块的三重挑战。在加密阶段，无线通信网络中的每个节点都在四元数分数阶 Meixner 矩 (QFOMM) 的帮助下分配一个公钥和私钥。在解密阶段，数字签名通过发送者的公钥解密为消息。区块挖掘与生成，采用绿色工作量证明机制，提升交易数据的安全性。所提出的方法是在以太坊和 Solidity 编程语言中实现的，而且这种功效是通过特定的性能矩阵来评估的，例如响应时间、CPU 时间、块创建时间、延迟、灵敏度、吞吐量、能源效率、计算成本和准确性。然后，与基于区块链的新兴隐私保护框架等现有方法相比，所提出的 BC-CS-AMSDAN-QFOMM-WCN 方法的性能提供了 23.31%、11.03%、27.89% 的更高吞吐量和 36.51%、13.09%、22.24% 的最小延迟6G 无线通信 (BC-CS-B-RAN-WCN)、无线通信和网络系统的区块链和机器学习 (BC-CS-DAG-ML-WCN) 以及多运营商无线通信网络的基于区块链的频谱共享交易(BC-CS-SS-TSS-WCN) 分别。