Trusted Data Access Control Based on Logistics Business Collaboration Semantics
Source abstract
Abstract
In the context of the digital evolution of the logistics industry, the interconnection of logistics information systems and associated data have become an obstacle of business collaboration among various stakeholders. A critical challenge in this domain is ensuring controllable access to logistics business data, given the industry’s current state characterized by independence, autonomy, disconnection, and heterogeneity, alongside the non-negotiable requirement for data privacy. We propose a novel model of trusted data access control based on of logistics business collaboration semantics. This approach incorporates semantic inference technologies into attribute-based access control mechanisms, thereby enabling the streamlined formulation of access control policies and facilitating unified authorization and control. Moreover, the method addresses the issue of access control policy management and maintenance at the semantic level. The proposed solution can pave the way for enhanced business collaboration between business entities, and further enable the building of a data exchange service platform within the logistics industry.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Access Control and Trust · Cloud Data Security Solutions · Business Process Modeling and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Information Science and Engineering, Linyi University, Linyi 276000, China
Department of Computer Science, University of California Davis, Davis, CA 94555, USA
Funding
Shandong Provincial Natural Science Foundation · National Natural Science Foundation of China · Development Plan of Youth Innovation Team in Universities of Shandong Province
References (36)
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