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Jingyu Zheng

dblp:380/1246 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
—ORCID · conflict

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

Artificial intelligence and machine learning · 1 · 1 since 2021Security 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 · 56% Cloud and datacenter computing · 44%
Network and information security
1 paper
Cryptographic primitives and cryptanalysis · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cryptographic primitives and cryptanalysis › cryptographic foundations › cryptographic commitments
polynomial commitment
1.012026
MPA: Lightweight and Updatable Integrity Auditing for Decentralized Storage Using Merkle Trees and Polynomial Commitments · IEEE Trans. Inf. Forensics Secur. 2026
Cloud and datacenter computing › cloud storage
data integrity auditing
1.012026
MPA: Lightweight and Updatable Integrity Auditing for Decentralized Storage Using Merkle Trees and Polynomial Commitments · IEEE Trans. Inf. Forensics Secur. 2026
Storage systems
storage reliability
1.012026
MPA: Lightweight and Updatable Integrity Auditing for Decentralized Storage Using Merkle Trees and Polynomial Commitments · IEEE Trans. Inf. Forensics Secur. 2026
Storage systems › distributed storage
decentralized storage
0.312026
MPA: Lightweight and Updatable Integrity Auditing for Decentralized Storage Using Merkle Trees and Polynomial Commitments · IEEE Trans. Inf. Forensics Secur. 2026

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

polynomial commitment · 2.0merkle tree · 2.0blockchain · 2.0
YearPublicationVenuePosition
2026 MPA: Lightweight and Updatable Integrity Auditing for Decentralized Storage Using Merkle Trees and Polynomial Commitments
abstract
With the growing demand for outsourcing data to decentralized storage systems, ensuring the integrity of out-sourced data becomes a critical challenge. Existing auditing schemes, however, often assume single-copy or centralized models, and suffer from inefficiency, lack of public verifiability, or poor scalability in multi-replica settings. To address these limitations, we propose MPA, a lightweight and publicly verifiable auditing scheme tailored for multi-copy cloud storage. By integrating polynomial commitment schemes with Merkle trees, our design achieves efficient block-level integrity verification while enabling dynamic updates. To mitigate collusion between cloud service providers, each data copy is uniquely encrypted, and the audit process supports simultaneous verification across multiple providers. Furthermore, we introduce an optimized batch auditing mechanism that allows the verifier to aggregate proofs across different files and providers, reducing both computation and communication overhead. To enhance audit transparency and unpredictability, we adopt a blockchain-assisted challenge generation protocol based on commit-and-reveal randomness. Theoretical analysis and performance evaluation demonstrate that MPA achieves strong security guarantees under standard assumptions, while significantly outperforming existing solutions in terms of efficiency and scalability.
Yongliang Xu, Hang Cheng, Jingyu Zheng, Xinpeng Zhang 0001, Huaxiong Wang
IEEE Trans. Inf. Forensics Secur.3
2024 Inter-structure and intra-semantics graph contrastive learning for disease prediction
Yan Kang 0003, Jingyu Zheng, Mingjian Yang
Knowl. Based Syst.2