The growth of the Internet of Things (IoT) has introduced significant security challenges, mainly due to the resource constraints of devices and the limitations of centralized architectures. This paper proposes a blockchain-based Zero-Trust framework for secure and scalable IoT systems. The approach is architecture-agnostic and combines decentralized identity management, hybrid data storage, and edge-assisted computation. To optimize resource usage, raw data are stored off-chain while cryptographic hashes are anchored on the blockchain, ensuring integrity and immutability. A Merkle tree structure is employed to aggregate data efficiently, reducing communication overhead and blockchain transaction costs. Experimental results demonstrate that lightweight cryptographic mechanisms, combined with Merkle-based aggregation, provide strong security guarantees with low energy consumption. The proposed framework achieves improved scalability, robustness, and efficiency, making it suitable for resource-constrained IoT environments.
Florian Bonelli, Alexandre dos Santos Roque, E. P. de Freitas· International Conference on...· 0 citations
Critical safety functions in modern vehicles rely heavily on intra-vehicle networks (IVNs), primarily via the Controller Area Network (CAN) protocol. The inherent vulnerabilities of CAN require robust intrusion detection systems (IDS) to mitigate adversarial threats. However, state-of-the-art IDS, especially AI-based approaches, often lack a comprehensive, well-defined performance analysis method. This work proposes and evaluates a structured pipeline for in-vehicle IDS, analyzing an autoencoder semi-supervised IDS as a practical case study. The method is validated on publicly available datasets, covering multiple attack types, with additional analysis of generalization capabilities. Performance is rigorously assessed using precision, recall, F1-score, and the Matthews Correlation Coefficient (MCC), chosen for its robustness in imbalanced scenarios. Results demonstrated highly efficient identification of DoS attacks (MCC 1.00), though Fuzzy DoS detection showed lower performance (MCC 0.214 in CAN-MIRGU and 0.074 in CAN-MODES). These findings support the viability of the proposed pipeline for IDS analysis focusing on enhancing CAN network security, consistent with recent research trends.
Lucas Melo da Silva Alves, Alexandre dos Santos Roque, E. P. de Freitas· International Conference on...· 0 citations