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Feng Jiang, Huai-Min Wang, Pei-Chang Shi, Xiang Fu, Liao-Liao Feng, Rui Li, Mo-Heng Lin. An Understandable Cross-Chain Authentication Mechanism for JointCloud Computing[J]. Journal of Computer Science and Technology. DOI: 10.1007/s11390-025-4733-4
Citation: Feng Jiang, Huai-Min Wang, Pei-Chang Shi, Xiang Fu, Liao-Liao Feng, Rui Li, Mo-Heng Lin. An Understandable Cross-Chain Authentication Mechanism for JointCloud Computing[J]. Journal of Computer Science and Technology. DOI: 10.1007/s11390-025-4733-4

An Understandable Cross-Chain Authentication Mechanism for JointCloud Computing

  • JointCloud Computing is a new computing paradigm that supports cloud services to achieve mutually beneficial outcomes. A key component of this model is jointcloud computing distributed ledger, which ensures trust among cloud entities with diverse interests by providing digital space evidence. Blockchain forms the foundation of this framework, and its adoption is growing in various fields to optimize workflows. However, challenges related to blockchain interoperability and cross-chain data authentication remain unresolved, hindering the broader establishment of trust among cloud entities. This paper focuses on the specific scenario of cross-chain data authentication and provides a secure and easy-to-deploy solution. Drawing on the concepts of relay chain and notary mechanism in cross-chain methods, our solution leverages smart contracts and on-chain proofs to ensure security, thereby reducing the reliance on relay nodes. In cases of data falsification, our approach offers mechanisms for accountability and data revocation, further enhancing security. Additionally, participating blockchains do not need to alter their data structures or network compositions for authentication, which makes the solution easy to deploy. Experimental results demonstrate that our design can be easily deployed on both homogeneous and heterogeneous blockchains. While maintaining performance comparable to existing solutions, it significantly enhances system security. In the event of data falsification, the solution can quickly hold individuals accountable and eliminate the impact of falsified data, reducing the time to mitigate the impact by half compared to other solutions.
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