Demo Data from SIGIR 2026 / reviewers in the wild / expert
Binru Dai
dblp:360/8827
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none
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.
| Network and information security
1 paper |
Blockchain and cryptocurrency security · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Distributed and cloud data management · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Blockchain and cryptocurrency security
blockchain analysis |
0.7 | 1 | 2023 | iQuery: A Trustworthy and Scalable Blockchain Analytics Platform · IEEE Trans. Dependable Secur. Comput. 2023 |
Distributed and cloud data management
blockchain query processing |
0.2 | 1 | 2023 | iQuery: A Trustworthy and Scalable Blockchain Analytics Platform · IEEE Trans. Dependable Secur. Comput. 2023 |
Methods — techniques the papers use, named apart from their topics
second opinion game · 1.3game theory · 1.3smart contracts · 0.7smart contract · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | iQuery: A Trustworthy and Scalable Blockchain Analytics PlatformabstractBlockchain, a distributed and shared ledger, provides a credible and transparent solution to increase application auditability by querying the immutable records written in the ledger. Unfortunately, existing query APIs offered by the blockchain are inflexible and unscalable. Some studies propose off-chain solutions to provide more flexible and scalable query services. However, the query service providers (SPs) may deliver fake results without executing the real computation tasks and collude to cheat users. In this article, we propose a novel intelligent blockchain analytics platform termediQuery, in which we design a game theory based smart contract to ensure the trustworthiness of the query results at a reasonable monetary cost. Furthermore, the contract introduces the second opinion game that employs a randomized SP selection approach coupled with non-ordered asynchronous querying primitive to prevent collusion. We achieve a fixed price equilibrium, destroy the economic foundation of collusion, and can incentivize all rational SPs to act diligently with proper financial rewards. In particular,iQuerycan flexibly support semantic and analytical queries for generic consortium or public blockchains, achieving query scalability to massive blockchain data. Extensive experimental evaluations show thatiQueryis significantly faster than state-of-the-art systems. Specifically, in terms of the conditional, analytical, and multi-origin query semantics,iQueryis 2 ×, 7 ×, and 1.5 × faster than advanced blockchain and blockchain databases. Meanwhile, to guarantee 100% trustworthiness, only two copies of query results need to be verified iniQuery, whileiQuery's latency is$2 \sim 134$× smaller than the state-of-the-art systems. Lingling Lu, Zhenyu Wen, Ye Yuan 0001, Binru Dai, Changting Lin, Qinming He, Zhenguang Liu, Jianhai Chen, Rajiv Ranjan 0001 |
IEEE Trans. Dependable Secur. Comput. | 4 |