Abstract
Applying blockchain technology to the Internet of Things (IoT) remains a huge challenge. To meet the actual needs of IoT, a lightweight and high-throughput consensus mechanism, combined with blockchain technology, is proposed in this study. Blockchain nodes use the Diffie–Hellman algorithm for key negotiation. Sensors and blockchain nodes can use the shared key to generate HMAC (Hash-based Message Authentication Code) signatures for sensor-aware transactions and use the Verifiable Random Function to implement block nodes. Offline fast election, which is the node that wins the election, becomes the block node. Machine learning methods are also introduced to identify or remove outliers in the sensor data before such data are uploaded to the chain. Experimental results show that the system throughput synchronously increases as the test load increases. Moreover, when the test load is 800 tps, the system throughput reaches the maximum, close to 600 tps. When the test load exceeds 800 tps, the actual system throughput starts to drop, and approximately 90% of transactions have a delay time within 5000 ms. This method can be used in a lightweight IoT system.
Highlights
With the continuous development and progress of technologies such as sensor technology, computer control technology, embedded technology, and wireless network data communication, the Internet of ings (IoT) has shown great development worldwide [1]
According to the characteristics of the IoT platform, blockchain technology can solve the security and management problems that a large amount of smart device data can appear in a centralized system framework [4]
Literature [9] proposed a new role and authority arbitration structure in IoT that is a fully distributed access control system for IoT based on blockchain technology and is evaluated in a real IoT scenario. e results provided in this article indicate that, in specific scalable IoT scenarios, blockchain technology can be used as an access control technology to enhance security
Summary
With the continuous development and progress of technologies such as sensor technology, computer control technology, embedded technology, and wireless network data communication, the Internet of ings (IoT) has shown great development worldwide [1]. According to the characteristics of the IoT platform, blockchain technology can solve the security and management problems that a large amount of smart device data can appear in a centralized system framework [4]. High-resource devices create an overlay network to implement a publicly accessible distributed blockchain, Shock and Vibration ensure end-to-end privacy and security, and use distributed authentication to reduce block verification processing time, which is implemented in smart home applications. Mainstream blockchain platforms usually use computationally intensive asymmetric key technology as user identification and transaction verification mechanism; one example is the secp256k1 elliptic curve asymmetric key pair used in Bitcoin and Ethereum [14], which requires more computing power than what most IoT devices can provide. E main contents include the research on cryptographic algorithms and mechanisms suitable for lightweight IoT devices to access the blockchain. We attempt to avoid excessive communication overhead, and we introduce machine learning methods to identify or remove outliers in sensor data before data are uploaded to the chain
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