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Juncai Chen

dblp:343/9929 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 93% Cloud and datacenter computing · 7%
Network and information security
1 paper
Blockchain and cryptocurrency security · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems › data reduction
data deduplication
1.012026
Enabling Cross-Clouds Encrypted Data Fine-Grained Deduplication and Recovery via Blockchain Systems · IEEE Trans. Dependable Secur. Comput. 2026
Storage systems › storage reliability
data recovery
1.012026
Enabling Cross-Clouds Encrypted Data Fine-Grained Deduplication and Recovery via Blockchain Systems · IEEE Trans. Dependable Secur. Comput. 2026
Storage systems › data reduction › data deduplication
encrypted deduplication
1.012026
Enabling Cross-Clouds Encrypted Data Fine-Grained Deduplication and Recovery via Blockchain Systems · IEEE Trans. Dependable Secur. Comput. 2026
Storage systems
storage reliability
1.012026
Enabling Cross-Clouds Encrypted Data Fine-Grained Deduplication and Recovery via Blockchain Systems · IEEE Trans. Dependable Secur. Comput. 2026
Cloud and datacenter computing
cloud storage
0.312026
Enabling Cross-Clouds Encrypted Data Fine-Grained Deduplication and Recovery via Blockchain Systems · IEEE Trans. Dependable Secur. Comput. 2026

Methods — techniques the papers use, named apart from their topics

vector commitment · 2.0smart contract · 2.0bloom filter · 2.0low-density parity-check code · 1.0low-density parity check code · 1.0
YearPublicationVenuePosition
2026 Enabling Cross-Clouds Encrypted Data Fine-Grained Deduplication and Recovery via Blockchain Systems
abstract
Data deduplication contributes to avoiding great waste of cloud storage resources. Most of current data deduplication schemes focus on file-level data deduplication, without realizing deduplication ownership privacy protection, data blocks retrieval or error data blocks recovery. To this end, this paper proposes cross-clouds encrypted data fine-grained deduplication and recovery (CC-FGDR) scheme supporting blockchain collaborative computing. CC-FGDR exploits two-party joint generation of deduplication tags to prevent deduplication privacy leakage, and constructs vector-commitment ciphertext tree to realize proofs of ownership verification of distributed backup data blocks via blockchain systems. CC-FGDR achieves secure cross-clouds deduplication detection by constructing twin bloom filter tree and privacy puncture pseudo-random function. To achieve data availability, a ciphertext reconstruction matrix is introduced and combined with countable bloom filter to achieve the location, search and retrieval of distributed outsourced data blocks. CC-FGDR further designs low-density parity check code to achieve cross-clouds encrypted error data recovery through collaborative computing of smart contracts. The security analysis demonstrates CC-FGDR ensures data storage verifiability, data confidentiality, and ownership privacy protection. Performance evaluation demonstrates the feasibility of CC-FGDR in the deployment of multiple clouds via blockchain systems, and CC-FGDR significantly improves the deduplication efficiency by joint deduplication in multi-clouds.
Bingyun Liu, Juncai Chen, Yinbin Miao, Jie Zhao 0015, Huaxiong Wang
IEEE Trans. Dependable Secur. Comput.3