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Xtreme Gradient Balloon Cryptographic Compressed Blockchain-Based Secure Routing in Cognitive Radio Networks

2026 · ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA) · Vol 12, pp. 816-831 · 0 citations

TL;DR

A novel blockchain method called, eXtreme Gradient Boost Quadratic Balloon Cryptographic Block Compression (XGBQ-BCBC) based secured routing in CRN is proposed, and the security of cognitive radio blockchain network is demonstrated to be improved in a significant manner.

Abstract

The inception of cognitive radio networks (CRNs) institutes both possibilities and complications in spectrum access and security. Blockchain technology has made an appearance as a possible solution to address these issues, providing improved transparency, security and effectiveness in spectrum management. Researchers propose several security methods to mitigate these attacks, each with drawbacks. Most of these methods have higher complexity, while others cannot be used to focus on training time and accuracy. To overcome these issues while maintaining higher security and Quality of Service (QoS), a novel blockchain method called, eXtreme Gradient Boost Quadratic Balloon Cryptographic Block Compression (XGBQ-BCBC) based secured routing in CRN is proposed. The method initially collects multiple secondary user and primary user from different cognitive radio controllers and creates blocks for the storage of these sets in blockchain network. Here, the eXtreme Gradient Boost Quadratic Node Classifier is employed where the weak classifier results are combined using Quadratic Classifier for classifying and authenticating the nodes as normal nodes or attacks based on the residual energy and relative trustworthiness factor and stored in the blockchain. At this point, the data packets collected from the normal nodes are hashed by using Balloon Cryptographic Matyas–Meyer–Oseas (MMO) Block compression function. Next, the hashed results are sent to the normal nodes by authenticating the normal nodes. If normal node’s authentication verification is passed, then the hashed results are said to the receiver nodes, therefore ensuring robust data transmission in the CRN. The simulation results of the proposed method demonstrate 27%, 32% data confidentiality and data integrity in the presence of MUs, when compared to other methods like Channel Availability Probability and multi-objective optimization. As a result the security of cognitive radio blockchain network is demonstrated to be improved in a significant manner.

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