The emergence of edge computing has expanded the scope of Internet of Things (IoT) cloud-terminal architecture. With the reduction of transmission and processing delays of massive data on terminal devices, it also brings new security issues. Aiming at the problem of data security and management issues between edge nodes of IoT and massive heterogeneous devices, and considering that blockchain technology is widely used in the security management of data in distributed systems, an IoT access control model Smart Contract for Attribute-Based Access Control (SC-ABAC) was proposed based on blockchain and edge computing. Firstly, an IoT access control architecture integrated with edge computing was proposed, and by combining smart contracts with Attribute-Based Access Control (ABAC), SC-ABAC was proposed and designed. Then, the optimization of Proof of Work (PoW) consensus algorithm and the access control management flow of SC-ABAC were given. Experimental results show that the time consumed by the proposed model increases linearly with the number of times under continuous access to the block, the Central Processing Unit (CPU) utilization rate is stable, and the CPU security is good during the continuous access process. In this model, the time consumption of calling contracts in the query process only increases linearly with the times, and the time consumptions of the strategy addition and judgment process are both constant. And the optimized consensus mechanism has about 18.37 percentage points less time consumption than PoW consensus per 100 blocks. Therefore, the proposed model can provide decentralized, fine-grained and dynamic access control management in the IoT environment, and can reach consensus faster in a distributed system to ensure data consistency.
This paper is about IoT security. In the cloud-edge-end architecture, try to implement access control based on blockchain and give a SC-ABAC model and a simple prototype. SC-ABAC is Smart Contract for Attribute-Based Access Control, and the POW consensus algorithm has been improved in the prototype.
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Until November 17, 2023, this paper was selected as a China Knowledge Network Academic Essentials Highly Cited Paper and Highly Downloaded Paper.