Privacy-Preserving IoT Big Data Collection: A Comparative Study of Hybrid BlockchainBased Architectures

Privacy-Preserving IoT Big Data Collection: A Comparative Study of Hybrid BlockchainBased Architectures Nirmalgοwri K Dr.S Sathya

The rapid growth of Internet of Things (IoT) applications has resulted in massive volumes of sensitive data, raising critical challenges related to privacy, scalability, and performance in traditional centralized data management architectures. Although blockchain technology offers decentralized trust and data integrity, blockchain-only IoT solutions suffer from high latency, limited scalability, and excessive storage overhead. To address these limitations, this paper presents a distributed hybrid architecture that integrates blockchain, edge computing, and privacy-preserving cryptographic mechanisms for secure IoT big data collection and processing. A comprehensive comparative analysis is conducted between the proposed hybrid model and existing centralized cloud, blockchain-only, and edge-only architectures using key performance metrics such as latency, throughput, storage overhead, energy consumption, scalability, and privacy preservation. Experimental results demonstrate that the proposed hybrid architecture reduces end-to-end latency by up to 54% compared to blockchain-only systems and by 28% compared to centralized architectures when evaluated with 1,000 IoT devices. The hybrid model achieves a throughput of 450 transactions per second, representing nearly a 5× improvement over blockchain-only solutions. Furthermore, blockchain storage overhead is reduced by approximately 74% through off-chain storage and selective on-chain metadata management.
2026 2026 7130 7137 10.35444/IJANA.2026.17506 https://www.ijana.in/papers/V17I5-6.pdf https://www.ijana.in/papers/V17I5-6.pdf