Hybrid Chain: Blockchain Enabled Framework for Bi-Level Intrusion Detection and Graph-Based Mitigation for Security Provisioning in Edge Assisted IoT Environment

Abstract

Internet of Things (IoT) is an emerging technology and its applications are flattering amidst many users, as it makes everything easier. As a consequence of its massive growth, security and privacy are becoming crucial issues where the IoT devices are perpetually vulnerable to cyber-attacks. To overcome this issue, intrusion detection and mitigation is accomplished which enhances the security in IoT networks. In this paper, we proposed Blockchain entrenched Bi-level intrusion detection and graph based mitigation framework named as HybridChain-IDS. The proposed work embrace four sequential processes includes timebased authentication, user scheduling and access control, bi-level intrusion detection and attack graph generation. Initially, we perform time-based authentication to authenticate the legitimate users using NIK-512 hashing algorithm, password and registered time are stored in Hybridchain which is an assimilation of blockchain and Trusted Execution Environment (TEE) which enhances data privacy and security. After that, we perform user scheduling using Cheetah Optimization Algorithm (COA) which reduces the complexity and then the access control is provided to authorized users by smart contract by considering their trust and permission level. Then, we accomplish bi-level intrusion detection using ResCapsNet which extracts sufficient features and classified effectively. Finally, risk of the attack is evaluated, and then the attacks graphs are generated by employing Enhanced k-nearest neighbor (KNN) algorithm to identify the attack path. Furthermore, the countermeasures are taken based on the attack risk level and the attack graph is stored in Hybridchain for eventual attack prediction. The implementation of this proposed work is directed by network simulator of NS-3.26 and the performance of the proposed HybridChain-IDS is enumerated based on various performance metrics.

BlockFog: A Blockchain-based Framework for Intrusion Defense in IOT Fog Computing

“…Additionally, by simulating network failures and disconnections, the robustness and reliability of BlockFog were put to the test. Concluding the study, a comparative lens was employed as BlockFog's performance was juxtaposed against two contemporary models, Hybridchain-IDS [24] and MZWB [20], highlighting its potential strengths and areas of refinement in the vast realm of IoT fog computing.…”

“…Reda Salama et al [23] proposed the BXAI-IDCUCS model, integrating blockchain with Explainable Artificial Intelligence for IoT security. AHMED A. M. SHARADQH et al [24] emphasized HybridChain-IDS, a model that combines blockchain, trusted execution environments, and machine learning for advanced IoT network security.…”

“…Its Device Onboarding & Identity Management feature further strengthens its position as the industry leader in IoT security solutions. BlockFog is contrasted with other models, specifically AHMED A. M. SHARADQH [24] and Salaheddine Kably et al [20]. The performance and potential of BlockFog in IoT security have been evaluated with the aid of these and other references.…”

MAC Protocol Based IoT Network Intrusion Detection Using Improved Efficient Shuffle Bidirectional COOT Channel Attention Network

“…Although advanced deep learning methods and transfer learning approaches are missing for enhancing robustness, accuracy, and energy consumption. Sharadqh et al [24] developed a hybrid chain framework for IoT networks, combining intrusion detection and graph-based mitigation. The architecture uses blockchain technology to provide a secure and decentralized environment for IoT devices.…”

Detection of DDoS attacks in SDN with Siberian Tiger Optimization algorithm and deep learning

“…In other words, by optimizing deep learning parameters, attacks are detected with less error [28,29]. Another challenge in detecting attacks in SDN networks is that data such as blacklists is exchanged between network switches with methods such as blockchain [30]. These approaches have significant time to exchange information due to their complexity.…”