Blockchain-Assisted Public Audit for Shared Data in Ad Hoc Networks
Researchers at the Xi'an University of Technology in Shaanxi, People's Republic of China, have developed a blockchain-assisted public audit with cross-authentication for shared data in Ad Hoc networks. This innovative solution provides a secure and decentralized mechanism for ensuring the integrity and privacy of shared data. The researchers have demonstrated the advantages of their scheme through security proof and extensive experiments.
Key Takeaways:
- The dynamic nature of Ad Hoc networks poses challenges to data security, requiring innovative solutions to prevent malicious storage servers from compromising data privacy and integrity.
- The blockchain-assisted public audit with cross-authentication for shared data in Ad Hoc networks uses an iterative hash chain structure to ensure a continuous, seamless flow of united authentication among parties over time.
- The scheme resists fraudulent owners, allows data users to audit shared data in a semi-non-interactive mode to reduce communication costs, and achieves decentralization by adopting blockchain rather than a third-party auditor (TPA) to prevent data disclosure.
- The research supports multiple public audits to maintain a sustainable integrity of the data, and allows users to audit shared data even in highly privacy-protective contexts where the owner's identity is anonymized.
- The scheme prevents malicious data owners from manipulating validation results and making the server liable for data corruption.
- The researchers propose a blockchain-assisted public audit with cross-authentication to address the challenge of a fraudulent data owner in public audits for shared data.
Statistics:
- 178: The number of the Ad Hoc Networks volume where the research was published.
- 2025: The year when the research was conducted and published.
- 10: The number of authors of the research, including Shangping Wang, Jifang Wang, Jin Sun, Xin Zhao, and Bintao He.
Sources:
- Ad Hoc Networks. 2025;178.
- Ad Hoc Networks. Can be contacted at Elsevier, Radarweg 29, 1043 Nx Amsterdam, Netherlands.
- Shangping Wang, Xi'an University of Technology, School of Sciences, Xian 710048, Shaanxi, People's Republic of China.
- Jifang Wang, Jin Sun, Xin Zhao, and Bintao He.