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Achieving Efficient and Privacy-Preserving Cross-Domain Big Data Deduplication in Cloud
- Source :
- IEEE Transactions on Big Data. 8:73-84
- Publication Year :
- 2022
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2022.
-
Abstract
- Secure data deduplication can significantly reduce the communication and storage overheads in cloud storage services, and has potential applications in our big data-driven society. Existing data deduplication schemes are generally designed to either resist brute-force attacks or ensure the efficiency and data availability, but not both conditions. We are also not aware of any existing scheme that achieves accountability, in the sense of reducing duplicate information disclosure (e.g., to determine whether plaintexts of two encrypted messages are identical). In this paper, we investigate a three-tier cross-domain architecture, and propose an efficient and privacy-preserving big data deduplication in cloud storage (hereafter referred to as EPCDD). EPCDD achieves both privacy-preserving and data availability, and resists brute-force attacks. In addition, we take accountability into consideration to offer better privacy assurances than existing schemes. We then demonstrate that EPCDD outperforms existing competing schemes, in terms of computation, communication and storage overheads. In addition, the time complexity of duplicate search in EPCDD is logarithmic.
- Subjects :
- Scheme (programming language)
Information Systems and Management
business.industry
Computer science
Distributed computing
020208 electrical & electronic engineering
Big data
Cloud computing
02 engineering and technology
Encryption
Computer security
computer.software_genre
Domain (software engineering)
0202 electrical engineering, electronic engineering, information engineering
Data deduplication
020201 artificial intelligence & image processing
business
Time complexity
computer
Cloud storage
Information Systems
computer.programming_language
Subjects
Details
- ISSN :
- 23722096
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Big Data
- Accession number :
- edsair.doi...........a3e8a249a319617bb335e4d8ef885f14