A Blockchain-Enabled Multi-Authority Secure IoT Data-Sharing Scheme with Attribute-Based Searchable Encryption for Intelligent Systems

• Published in: Sensors
• Main Authors: Fu Zhang, Xueyi Xia, Hongmin Gao, Zhaofeng Ma, Xiubo Chen
• Format: Article
• Language: English
• Published: MDPI AG 2025-09-01
• Subjects: Internet of Things; blockchain; multi-authority; attribute-based searchable encryption; security
• Online Access: https://www.mdpi.com/1424-8220/25/19/5944

With the advancement of technologies such as 5G, digital twins, and edge computing, the Internet of Things (IoT) as a critical component of intelligent systems is profoundly driving the transformation of various industries toward digitalization and intelligence. However, the exponential growth of network connection nodes has expanded the attack exposure surface of IoT devices. The IoT devices with limited storage and computing resources struggle to cope with new types of attacks, and IoT devices lack mature authorization and authentication mechanisms. It is difficult for traditional data-sharing solutions to meet the security requirements of cloud-based shared data. Therefore, this paper proposes a blockchain-based multi-authority IoT data-sharing scheme with attribute-based searchable encryption for intelligent system (BM-ABSE), aiming to address the security, efficiency, and verifiability issues of data sharing in an IoT environment. Our scheme decentralizes management responsibilities through a multi-authority mechanism to avoid the risk of single-point failure. By utilizing the immutability and smart contract function of blockchain, this scheme can ensure data integrity and the reliability of search results. Meanwhile, some decryption computing tasks are outsourced to the cloud to reduce the computing burden on IoT devices. Our scheme meets the static security and IND-CKA security requirements of the standard model, as demonstrated by theoretical analysis, which effectively defends against the stealing or tampering of ciphertexts and keywords by attackers. Experimental simulation results indicate that the scheme has excellent computational efficiency on resource-constrained IoT devices, with core algorithm execution time maintained in milliseconds, and as the number of attributes increases, it has a controllable performance overhead.