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Chunfei Pan

dblp:424/9206 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2026
0009-0002-8300-4404ORCID · reported

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

Security and privacy · 1 · 1 first-author · 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 · 75% Cloud and datacenter computing · 25%
Network and information security
1 paper
Blockchain and cryptocurrency security · 100%

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

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing
cloud storage
1.012026
Blockchain-Enabled Efficient Deduplication and Mixed Auditing for Dynamic Cloud Data · IEEE Trans. Dependable Secur. Comput. 2026
Storage systems
data auditing
1.012026
Blockchain-Enabled Efficient Deduplication and Mixed Auditing for Dynamic Cloud Data · IEEE Trans. Dependable Secur. Comput. 2026
Storage systems › data reduction
data deduplication
1.012026
Blockchain-Enabled Efficient Deduplication and Mixed Auditing for Dynamic Cloud Data · IEEE Trans. Dependable Secur. Comput. 2026
Storage systems
storage reliability
1.012026
Blockchain-Enabled Efficient Deduplication and Mixed Auditing for Dynamic Cloud Data · IEEE Trans. Dependable Secur. Comput. 2026
Blockchain and cryptocurrency security
blockchain-based auditing
0.312026
Blockchain-Enabled Efficient Deduplication and Mixed Auditing for Dynamic Cloud Data · IEEE Trans. Dependable Secur. Comput. 2026

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

message-locked encryption · 2.0merkle hash tree · 2.0homomorphic verifiable tags · 2.0elliptic curve cryptography · 2.0
YearPublicationVenuePosition
2026 Blockchain-Enabled Efficient Deduplication and Mixed Auditing for Dynamic Cloud Data
abstract
As cloud storage is extensively utilized in the contemporary digital age, assuring data integrity and conserving cloud storage space has become a priority for all. However, existing cross-user deduplication audit schemes conflict with the pay-as-you-go model, causing unnecessary costs and violating data isolation. Moreover, retaining a single copy of identical data across multiple users introduces maintenance challenges during data operations. To address these issues, we propose a new blockchain-enabled efficient deduplication and mixed auditing scheme which intricately integrates Message-Locked Encryption (MLE) to construct Homomorphic Verifiable Tags (HVTs), enabling deduplication without exposing confidential data. Our scheme supports single-user deduplication at both block and file levels, as well as plaintext-ciphertext mixed auditing, thereby preventing redundant payments while preserving data isolation to simplify maintenance during data operations and ownership transfers. By employing Elliptic Curve Cryptography (ECC) to encrypt keys and storing the encrypted keys on the blockchain, we ensure data confidentiality while reducing the burden of local key management. Leveraging blockchain-based smart contracts, we further design a self-auditing mechanism that eliminates reliance on trusted third-party auditors. Moreover, our scheme embraces dynamic data operations through an optimized Merkle Hash Tree (MHT) and enables secure cloud data ownership transfer via identity verification. Finally, we prove the correctness and security of our scheme and evaluate its performance through experiments and comparisons with state-of-the-art works, demonstrating its efficiency, particularly in the data upload phase.
Chunfei Pan, Lei Zhou 0026, Anmin Fu, Zhenzhu Chen, Huaqun Wang, Yifeng Zheng 0001, Yansong Gao 0001
IEEE Trans. Dependable Secur. Comput.1