Demo Data from VLDB 2026 / reviewers in the wild / expert
Yue Zhang 0035
dblp:47/722-35
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2020
0000-0002-9195-6782ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 1 · 1 first-author
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 |
Cloud and datacenter computing · 100% | |
| Network and information security
1 paper |
Cryptographic primitives and cryptanalysis · 50% Authentication and access control · 50% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cryptographic primitives and cryptanalysis › public-key cryptography
identity-based cryptography |
0.4 | 1 | 2020 | Enabling Efficient User Revocation in Identity-Based Cloud Storage Auditing for Shared Big Data · IEEE Trans. Dependable Secur. Comput. 2020 |
Authentication and access control › identity management
user revocation |
0.4 | 1 | 2020 | Enabling Efficient User Revocation in Identity-Based Cloud Storage Auditing for Shared Big Data · IEEE Trans. Dependable Secur. Comput. 2020 |
Cloud and datacenter computing
cloud storage |
0.4 | 1 | 2020 | Enabling Efficient User Revocation in Identity-Based Cloud Storage Auditing for Shared Big Data · IEEE Trans. Dependable Secur. Comput. 2020 |
Cloud and datacenter computing › cloud storage
storage auditing |
0.4 | 1 | 2020 | Enabling Efficient User Revocation in Identity-Based Cloud Storage Auditing for Shared Big Data · IEEE Trans. Dependable Secur. Comput. 2020 |
Cloud and datacenter computing › cloud storage
shared data auditing |
0.1 | 1 | 2020 | Enabling Efficient User Revocation in Identity-Based Cloud Storage Auditing for Shared Big Data · IEEE Trans. Dependable Secur. Comput. 2020 |
Methods — techniques the papers use, named apart from their topics
private key update · 0.9identity-based cryptography · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Enabling Efficient User Revocation in Identity-Based Cloud Storage Auditing for Shared Big DataabstractCloud storage auditing schemes for shared data refer to checking the integrity of cloud data shared by a group of users. User revocation is commonly supported in such schemes, as users may be subject to group membership changes for various reasons. Previously, the computational overhead for user revocation in such schemes is linear with the total number of file blocks possessed by a revoked user. The overhead, however, may become a heavy burden because of the sheer amount of the shared cloud data. Thus, how to reduce the computational overhead caused by user revocations becomes a key research challenge for achieving practical cloud data auditing. In this paper, we propose a novel storage auditing scheme that achieves highly-efficient user revocation independent of the total number of file blocks possessed by the revoked user in the cloud. This is achieved by exploring a novel strategy for key generation and a new private key update technique. Using this strategy and the technique, we realize user revocation by just updating the non-revoked group users' private keys rather than authenticators of the revoked user. The integrity auditing of the revoked user's data can still be correctly performed when the authenticators are not updated. Meanwhile, the proposed scheme is based on identity-base cryptography, which eliminates the complicated certificate management in traditional Public Key Infrastructure (PKI) systems. The security and efficiency of the proposed scheme are validated via both analysis and experimental results. Yue Zhang 0035, Jia Yu 0003, Rong Hao, Cong Wang 0001, Kui Ren 0001 |
IEEE Trans. Dependable Secur. Comput. | 1 |