Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data.

Keon Attarha

dblp:421/4354 · DBLP profile ↗
← Back
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

TopicWeightPapersLastEvidence papers
Distributed systems › fault tolerance
byzantine fault tolerance
0.912025
DAG of DAGs: Order-Fairness Made Practical · Proc. ACM Manag. Data 2025
Distributed systems
consensus
0.912025
DAG of DAGs: Order-Fairness Made Practical · Proc. ACM Manag. Data 2025
Distributed systems › fault tolerance › byzantine fault tolerance
DAG-based consensus
0.912025
DAG of DAGs: Order-Fairness Made Practical · Proc. ACM Manag. Data 2025
Distributed systems › consensus › byzantine agreement
order-fairness
0.912025
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
YearPublicationVenuePosition
2025 DAG of DAGs: Order-Fairness Made Practical
abstract
Ensuring 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. Data4