Demo Data from VLDB 2026 / reviewers in the wild / expert
Matthew Keating
dblp:364/6987
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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.
| Network and information security
1 paper |
Cryptographic primitives and cryptanalysis · 77% Privacy and data protection · 23% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 50% Cloud and datacenter computing · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cryptographic primitives and cryptanalysis
obfuscation |
0.7 | 1 | 2023 | Architecture for Confidential Digital Asset Transfer on Blockchain Through Obfuscation · ICNP 2023 |
Privacy and data protection
anonymization |
0.2 | 1 | 2023 | Architecture for Confidential Digital Asset Transfer on Blockchain Through Obfuscation · ICNP 2023 |
Distributed systems
blockchain |
0.2 | 1 | 2023 | Architecture for Confidential Digital Asset Transfer on Blockchain Through Obfuscation · ICNP 2023 |
Cloud and datacenter computing
data market |
0.2 | 1 | 2023 | Architecture for Confidential Digital Asset Transfer on Blockchain Through Obfuscation · ICNP 2023 |
Methods — techniques the papers use, named apart from their topics
time-delays · 1.3one-time users · 1.3batch requests · 1.3anonymization · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Architecture for Confidential Digital Asset Transfer on Blockchain Through ObfuscationabstractBlockchains and related applications continue to grow as an area of technology that can provide advantages over traditional approaches in certain use cases. One such area are data markets. Data market use cases include secure asset transactions, data lineage and data governance between multiple parties and involves data security, immutability, transparency. Data markets require strong privacy guarantees for digital asset procurement. The inherent properties of a blockchain can provide significant benefits in the data-market use case. In fact, there are many commercial platforms currently leveraging blockchain technologies for blockchain-based data markets. Leveraging blockchain for data market use cases creates the opportunity for new logical architectures to preserve privacy in the blockchain ecosystem. This publication proposes a multi-faceted solution for stronger privacy guarantees for digital asset procurement on blockchain-based data markets. An architecture will be detailed which provides better guarantees of privacy to those acquiring digital asserts from blockchain-based data markets by leveraging time-delays, batch requests, anonymization, and virtual “one-time” users to form a layer of obfuscation around requests. Alan Barnett, Matthew Keating, Sean Ahearne |
ICNP | 2 |