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Can I read An Arbitrable Outsourcing Data Audit Scheme Supporting Credit Reward and Punishment and Multi-user Sharing on EtoBox?
An Arbitrable Outsourcing Data Audit Scheme Supporting Credit Reward and Punishment and Multi-user Sharing by Junfeng Tian; Qian Yang is a Computer Science article available to read on EtoBox.
What is An Arbitrable Outsourcing Data Audit Scheme Supporting Credit Reward and Punishment and Multi-user Sharing about?
In the era of the Internet of Things, cloud storage allows users to outsource their data without retaining a local copy. However, a serious problem caused by this pattern is that the data owner loses control of the data. In this case, to ensure outsourced storage data integrity, researchers proposed Provable Data Possession. However, most systems cannot deal with disagreements between entities throughout the process. Due to this, we propose an auditing system for outsourced data. By using undeniable blockchain information, it solves disputes between entities and avoids accounting delays by third-party auditors. A credit chain based on the public blockchain is designed. A novel dynamic credit calculation algorithm is adopted in the credit chain to realize an effective reward and punishment mechanism. Security proofs are provided in detail for the proposed scheme. Evaluation experiments show that compared with existing similar schemes, the scheme achieves arbitrable audit and has a lower computational cost.
Who reads An Arbitrable Outsourcing Data Audit Scheme Supporting Credit Reward and Punishment and Multi-user Sharing?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Junfeng Tian; Qian Yang
- Publisher
- Elsevier BV
- Published
- 2023
- Language
- EN
- Field
- Computer Science (Physical Sciences)