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Journal article
BA-AMST: A blockchain-assisted anonymous and multi-keyword searchable-traceable data sharing system in Industrial Internet of Things
Engineering science and technology, an international journal, Vol.66, 102055
2025
Abstract
With the widespread adoption of Industrial Internet of Things (IIoT) technologies and the rapid advancement of cloud storage, enterprises and users have benefited greatly from the convenience of industrial data sharing. A crucial initial step in this process is the ability to perform fast and efficient keyword searches to help users locate the required data within vast datasets. However, the risk of privacy breaches, the presence of malicious actors, and untrusted cloud servers pose significant threats to both individuals and primary data custodians. Ensuring equitable and precise data searches, while safeguarding sensitive industrial data, is therefore of paramount importance in industrial data-sharing systems. To address these challenges, this paper proposes a dynamic, anonymous, and traceable multi-keyword search scheme that integrates attribute-based encryption (ABE) with blockchain technology. A tracing algorithm is introduced to prevent private key leakage, and a Bloom filter is employed to conceal confidential access policies, preserving user privacy. Blockchain is utilized to generate user identities and record interactions between users and the system, ensuring fair search results, enhancing system security, and maintaining data integrity. To improve practicality, we introduce a fine-grained matching algorithm capable of generating four distinct types of feedback based on user-submitted information. Performance evaluations and security analyses demonstrate the solution’s multifunctionality and high efficiency, highlighting its potential for industrial applications.
Details
- Title
- BA-AMST: A blockchain-assisted anonymous and multi-keyword searchable-traceable data sharing system in Industrial Internet of Things
- Authors/Creators
- Leyou Zhang - Xidian UniversityRunze Tian - Xidian UniversityQing Wu - Xi’an University of Posts and TelecommunicationsFatemeh Rezaeibagha - Murdoch University, Centre for Healthy Ageing
- Publication Details
- Engineering science and technology, an international journal, Vol.66, 102055
- Publisher
- Elsevier B.V.
- Number of pages
- 15
- Identifiers
- 991005765132607891
- Copyright
- © 2025 The Authors.
- Murdoch Affiliation
- School of Information Technology
- Language
- English
- Resource Type
- Journal article
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- Web Of Science research areas
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