Decentralized big data auditing for smart city environments leveraging blockchain technology
Open accessAbstract
The idea of big data has gained extensive attention from governments and academia all over the world. It is especially relevant for the establishment of a smart city environment combining complex heterogeneous data with data analytics and artificial intelligence (AI) technology. Big data is generated from many facilities and sensor networks in smart cities and often streamed and stored in the cloud storage platform. Ensuring the integrity and subsequent auditability of such big data is essential for the performance of AI-driven data analysis. Recent years has witnessed the emergence of many big data auditing schemes that are often characterized by third party auditors (TPAs). However, the TPA is a centralized entity, which is vulnerable to many security threats from both inside and outside the cloud. To avoid this centralized dependency, we propose a decentralized big data auditing scheme for smart city environments featuring blockchain capabilities supporting improved reliability and stability without the need for a centralized TPA in auditing schemes. To support this, we have designed an optimized blockchain instantiation and conducted a comprehensive comparison between the existing schemes and the proposed scheme through both theoretical analysis and experimental evaluation. The comparison shows that lower communication and computation costs are incurred with our scheme than with existing schemes.
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The collaborative framework for smart cities in Ref. [106] has not had implementation of smart contract and security assessment done.
“However, the implementation of smart contract and security assessment has not been done.”
From A survey on the adoption of blockchain in IoT: challenges and solutions (2021) · cites this paper as [106]
If all transaction data are stored on chain, blockchain capacity will become very large to maintain over time.
“Moreover, if all transaction data are stored on chain, the blockchain capacity will become very large to maintain on the chain over time [289].”
From Blockchain for 5G and beyond networks: A state of the art survey (2020) · cites this paper as [289]
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- Authors
- Yu, H., Yang, Z., & Sinnott, R. O.
- Affiliations
- The University of Melbourne (AU)
- Beijing University of Technology (CN)
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 6288-6296
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2905871206
- Cited by
- 130
- References
- 28
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 16 · 2023: 25 · 2022: 28 · 2021: 21 · 2020: 21 · 2019: 5
- FWCI
- 18.95
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China (61671030)
- National Key R&D Program of China (2016YFB0801100, 2018YFB0803600)
- Industrial Internet Innovation Development Project
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
- Keywords
- big data auditing, smart cities, blockchain, decentralized auditing, third-party auditor, data integrity, cloud data security, sensor networks, communication and computation cost
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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