IoT + Blockchain
Research Papers
Academic and industry research
Blockchain and Federated Learning-based Intrusion Detection Approaches for Edge-enabled Industrial IoT Networks: A Survey
ResearchGate
This survey explores the integration of blockchain technology and federated learning to enhance intrusion detection systems (IDS) in industrial IoT (IIoT) networks. As industrial systems become increasingly interconnected, they face advanced persistent threats that static security measures cannot easily mitigate. The paper details how blockchain can provide a tamper-proof logging mechanism for IDS results, while federated learning enables collaborative model training across edge devices without compromising local data privacy. The authors categorize current methodologies, highlighting how this hybrid approach addresses the challenges of data sparsity and security in industrial settings. The study serves as a foundational resource for understanding how decentralized intelligence can augment cybersecurity posture in high-stakes environments, emphasizing the synergy between privacy-preserving machine learning and immutable verification.
Consensus Mechanism of IoT Based on Blockchain Technology
Wu
This paper investigates the adaptation of blockchain consensus mechanisms to the specific requirements of IoT environments. The authors analyze common consensus models, including Proof-of-Work, Proof-of-Stake, and Delegated Proof-of-Stake, identifying their limitations when applied to decentralized IoT networks. The central contribution is a proposed consensus model that balances the trade-offs between node energy consumption, security, and network speed. Through a detailed analysis, the study explores how the network topology of IoT devices influences the efficiency of consensus. The paper concludes by outlining potential paths for future implementation, emphasizing the need for flexible, adaptive consensus mechanisms that can handle the unique dynamics of intermittent connectivity and variable device power in IoT ecosystems.
A scalable blockchain based framework for efficient IoT data management using lightweight consensus
Scientific Reports
This paper addresses the critical bottleneck of scalability in blockchain-based IoT ecosystems. The researchers propose a novel, lightweight consensus mechanism specifically designed to handle the high-throughput, low-latency requirements of IoT sensor networks. By reducing the computational overhead typically associated with traditional Proof-of-Work or Proof-of-Stake protocols, the framework enables efficient data management and verification at the edge of the network. The study evaluates the performance metrics of this framework against existing blockchain models, demonstrating improvements in energy efficiency, transaction latency, and storage overhead. It contributes to the field by offering a practical, scalable solution that maintains the security guarantees of a blockchain while accommodating the limitations of resource-constrained IoT hardware.