A Blockchain‐Based Secure Routing Model in Autonomous Systems Using Hybrid Mexican Axolotl With Sailfish Optimizer

The traditional interdomain routing safety measures, greatly dependent on reactive anomaly identification and mitigation, face difficulty in efficiently opposing the rising incidence of prefix hijacking, autonomous systems (AS)‐path forgery, and route leaks, which considerably threaten the stability of the Internet. This work introduces a novel blockchain‐based model suggesting smart contracts to offer a practical and reliable routing system, thus improving interdomain routing protection and authentication. The significance of this work lies in its proactive approach to securing routing processes, addressing the limitations of existing reactive methods that have proven insufficient in mitigating the impacts of routing anomalies. This article provides trusted routing in autonomous paradigms of soft computing based on blockchain to enhance routing security, authentication, and validation. Here, the performance of the routing is executed via a developed hybrid Mexican axolotl with sailfish optimizer (HMASO). Further, the blockchain is used as a distributed, traceable ledger and tamper‐proof for consistently storing the Internet number's distribution resources and creating a method for route origin verification with the major intention of routing security, authentication, and validation. The blockchain‐based routing model that has been developed allows independent work without any difficulties by decoupling the information needed for route validation, security, and authentication from routing models. The route selection is done by the developed HMASO algorithm to enhance the performance of the route validation, path loss, latency, and throughput. The framework demonstrates a robust mechanism for route origin and propagation validation, significantly reducing the risk of routing incidents. Experimental results reveal that the proposed model not only enhances security but also maintains high performance in route verification within acceptable limits across various Autonomous System scales. The numerical results showed that the existing TB‐BP attains 84.5 KBPS of throughput and 100 dB of path loss, which significantly hinders the speed and effectiveness of the model, significantly hinder practical applications and overall system accessibility. However, the proposed model gains a throughput of 94.51, a considerably reduced path loss of 5 dB in a model with 200 nodes, and a decreased latency of 0.5 s, when considering 50 nodes, leading to quicker routing and enhanced receptiveness. Therefore, the designed HMASO algorithm achieves superior performance as compared to other existing methods.