Demo Data from EDBT 2026 / reviewers in the wild / expert
Avi Asayag
dblp:227/7786
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2 · 1 first-author · 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 |
Cryptographic protocols and secure computation · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cryptographic protocols and secure computation › distributed randomness
randomness beacon |
0.3 | 1 | 2018 | A Fair Consensus Protocol for Transaction Ordering · ICNP 2018 |
Cryptographic protocols and secure computation › threshold cryptography
threshold decryption |
0.3 | 1 | 2018 | A Fair Consensus Protocol for Transaction Ordering · ICNP 2018 |
Distributed systems › consensus
blockchain consensus |
0.3 | 1 | 2018 | A Fair Consensus Protocol for Transaction Ordering · ICNP 2018 |
Distributed systems
consensus |
0.3 | 1 | 2018 | A Fair Consensus Protocol for Transaction Ordering · ICNP 2018 |
Distributed systems › consensus
committee election |
0.1 | 1 | 2018 | A Fair Consensus Protocol for Transaction Ordering · ICNP 2018 |
Methods — techniques the papers use, named apart from their topics
threshold decryption · 0.7correlated sampling · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Helix: A Fair Blockchain Consensus Protocol Resistant to Ordering ManipulationabstractWe presentHelix, a blockchain-based consensus protocol forfairordering of transactions among nodes in a distributed network. Helix advances in rounds, in each an elected primary node proposes a potential block (a successive set of transactions). For being included in the blockchain, a block must pass validation by an elected committee of nodes. Nodes have two primary preferences. First, to be elected as committee members. Additionally, because each transaction is associated with one of the network nodes, nodes would like to prioritize their own transactions over those of others. Our definition of fairness incorporates three key elements. First, the process of electing nodes to committees is random and unpredictable. Second, a correlated sampling scheme is used to guarantee random selection and ordering of pending transactions in blocks. Third, transactions are encrypted to hide their associations with nodes and prevent censorship. Through the corresponding threshold decryption process we obtain an unpredictable and non-manipulable randomness beacon, which serves both the election process and the correlated sampling scheme. We define a quantitative measure of fairness in the protocol, prove theoretically that fairness manipulation in Helix is significantly limited, and present experiments evaluating fairness in practice. David Yakira, Avi Asayag, Gad Cohen, Ido Grayevsky, Maya Leshkowitz, Ori Rottenstreich, Ronen Tamari |
IEEE Trans. Netw. Serv. Manag. | 2 |
| 2018 | A Fair Consensus Protocol for Transaction OrderingabstractWe present Helix, a blockchain-based consensus protocol for fair ordering of transactions among nodes in a distributed network. Helix advances in rounds, where in each round, the primary node (elected among the network nodes) proposes a potential block (a successive set of transactions). In order to be included in the blockchain, a block must pass validation by an elected committee of nodes. Helix nodes are presumed to have two primary preferences. They prefer to be elected as committee members. Additionally, because each transaction is associated with one of the network nodes, they prefer to prioritize their own transactions over those of others. In light of these individual preferences, our definition of fairness incorporates three key elements. First, the process of electing nodes to committees is random and unpredictable. Second, a correlated sampling scheme is used in order to guarantee random selection and ordering of pending transactions in blocks. Third, transactions are encrypted in order to hide their associations with their respective nodes and prevent censorship. Through the corresponding threshold decryption process we obtain an unpredictable and non-manipulable randomness beacon, which serves both the election process and the correlated sampling scheme. We define a quantitative measure of fairness in the protocol, prove theoretically that fairness manipulation in Helix is significantly limited, and present experiments evaluating fairness in practice. Avi Asayag, Gad Cohen, Ido Grayevsky, Maya Leshkowitz, Ori Rottenstreich, Ronen Tamari, David Yakira |
ICNP | 1 |