Demo Data from EDBT 2026 / reviewers in the wild / expert
Kushaz Sehgal
dblp:420/7841
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0008-4657-5578ORCID · reported
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 |
Cryptographic protocols and secure computation · 60% Blockchain and cryptocurrency security · 20% Cryptographic primitives and cryptanalysis · 20% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Blockchain and cryptocurrency security › privacy-preserving blockchain
mempool privacy |
0.9 | 1 | 2025 | Silent Threshold Traitor Tracing & Enhancing Mempool Privacy · CCS 2025 |
Cryptographic protocols and secure computation
threshold cryptography |
0.9 | 1 | 2025 | Silent Threshold Traitor Tracing & Enhancing Mempool Privacy · CCS 2025 |
Cryptographic primitives and cryptanalysis › public-key cryptography › public-key encryption
threshold encryption |
0.9 | 1 | 2025 | Silent Threshold Traitor Tracing & Enhancing Mempool Privacy · CCS 2025 |
Cryptographic protocols and secure computation › traitor tracing
threshold traitor tracing |
0.9 | 1 | 2025 | Silent Threshold Traitor Tracing & Enhancing Mempool Privacy · CCS 2025 |
Cryptographic protocols and secure computation
traitor tracing |
0.9 | 1 | 2025 | Silent Threshold Traitor Tracing & Enhancing Mempool Privacy · CCS 2025 |
Methods — techniques the papers use, named apart from their topics
threshold encryption · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Silent Threshold Traitor Tracing & Enhancing Mempool PrivacyabstractThe rising commerciality of cryptocurrencies and blockchains in DeFi applications raises the importance of implementing robust methods to protect its regular users against parties with enormous amounts of resources that allows them to balefully influence the market through various Maximal Extractable Value (MEV) strategies. There are typical situations in such scenarios where an end-user may want to hide its transaction details till it has been executed. Ensuring the privacy of pending mempool transactions thus becomes an important goal. To this end, various decentralized versions of threshold encryption (TE) systems have been recently shown particularly effective. Anirban Chakrabarti, Monosij Maitra, Arup Mondal, Kushaz Sehgal |
CCS | 4 |