EDBT 2026 Demo / reviewers in the wild / expert
Keon Attarha
dblp:421/4354
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0008-0208-9818ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 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 |
Distributed systems · 100% | |
| Network and information security
1 paper |
Blockchain and cryptocurrency security · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed systems › fault tolerance
byzantine fault tolerance |
0.9 | 1 | 2025 | DAG of DAGs: Order-Fairness Made Practical · Proc. ACM Manag. Data 2025 |
Distributed systems
consensus |
0.9 | 1 | 2025 | DAG of DAGs: Order-Fairness Made Practical · Proc. ACM Manag. Data 2025 |
Distributed systems › fault tolerance › byzantine fault tolerance
DAG-based consensus |
0.9 | 1 | 2025 | DAG of DAGs: Order-Fairness Made Practical · Proc. ACM Manag. Data 2025 |
Distributed systems › consensus › byzantine agreement
order-fairness |
0.9 | 1 | 2025 | DAG of DAGs: Order-Fairness Made Practical · Proc. ACM Manag. Data 2025 |
Methods — techniques the papers use, named apart from their topics
wave-based leader election · 1.7concurrent block proposal · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | DAG of DAGs: Order-Fairness Made PracticalabstractEnsuring order-fairness in distributed data management systems deployed in untrustworthy environments is crucial to prevent adversarial manipulation of transaction ordering, particularly in unpredictable markets where transaction order directly influences financial outcomes. While Byzantine Fault-Tolerant (BFT) consensus protocols guarantee safety and liveness, they inherently lack mechanisms to enforce order-fairness, exposing distributed systems to attacks such as frontrunning and sandwiching. Previous attempts to integrate order-fairness have often introduced substantial performance overhead, largely due to limitations of the underlying consensus protocols. This paper presents DAG of DAGs (DoD), a high-performance order-fairness protocol designed on top of DAG-based BFT consensus protocols. By leveraging the high throughput and resilience of DAG-based protocols, DoD addresses the performance limitations of existing order-fairness solutions. DoD's novel DAG of DAGs architecture enables seamless integration of order fairness with BFT consensus protocols. Through concurrent block proposals and a wave-based leader election mechanism, DoD significantly improves resilience against adversarial manipulation. A prototype implementation and experimental evaluation demonstrate that DoD effectively provides order fairness with minimal performance overhead. Heena Nagda, Sidharth Sankhe, Sakshi Sinha, Keon Attarha, Mohammad Javad Amiri, Boon Thau Loo |
Proc. ACM Manag. Data | 4 |