DeFiプライバシーを形作る11人の主要研究者：ダークプール、MPC、ZK、DP、コンプライアンス、MEVプライバシー。任意のカードをクリックして完全なプロフィールを展開します。
カードをクリックして詳細プロフィールを展開します。学派の色： Cornell IC3 · JPM AI 研究 · Bristol/KU Leuven · Edinburgh/IOG · Stanford/NYU · Gauntlet · Ethereum Foundation
SVG関係図。太い線 = 指導教官-学生。破線 = 影響関係。実線 = 共著/協働。ノードの色は学派コーディングに従います。
7つの研究学派。学派の色はすべてのビュー間で統一されています。
Pioneered TEE-based blockchain privacy and MEV/mempool analysis. Institutional origin of Flashbots and Chainlink's research culture.
Only school with confirmed production deployments. Prime Match (2021) and Atlas-X (2022–2024) are the only MPC/DP dark pools in live trading.
Finance side (Cartlidge) + crypto side (Smart) collaborate across Bristol-KU Leuven boundary. MP-SPDZ is the infrastructure layer used by most dark pool MPC papers globally.
Cardano/IOG academic arm. Created the template for regulated CBDC with threshold issuance and the PPB design language for compliance.
Grouped by primary research methodology (following the typology in research-methodology-typology.md). 研究ers may span multiple styles.
Theorem-proof style. UC simulation-based security. No implementation required; the goal is impossibility results and security definitions.
Real on-chain data, mempool traces, live exchange order books. Results are datasets and statistical analysis, not proofs.
Working prototypes with performance benchmarks. The question is: does this work in practice at acceptable speed?
Agent-based simulation of market dynamics. ABIDES as the primary vehicle — synthetic but calibrated to real exchange behavior.
Live system in production. The rarest category — requires crossing the academic-industry boundary with institutional backing.
Framing and positioning work. Creates the conceptual vocabulary that other researchers and regulators use.
Major papers from these 11 researchers, 2017–2025. Green dot = production deployment.
A curated entry sequence for someone new to DeFi privacy research. Each step unlocks the next.
Start with Flash Boys 2.0 (Daian, Juels et al., S&P 2020). This establishes why privacy matters in DeFi: the mempool is an information vector. Frontrunning, sandwich attacks, and arbitrage all stem from observable transaction intent.
Before reading privacy solutions, understand what they are solving. MEV is the threat model that motivates most dark pool research.
Read "The Dark Side of the Moon" (Cartlidge, Smart, 2019) to understand how MPC (specifically MP-SPDZ) can implement a private dark pool. Then read Turquoise Plato Uncross (2020) to see how real exchange specifications constrain MPC design.
Cartlidge provides the market microstructure intuition; Smart provides the MPC infrastructure. Understanding both lets you evaluate any subsequent dark pool paper.
Read Tesseract (Juels et al., CCS 2019) for the alternative architecture using Intel SGX. Compare TEE's trust assumptions (hardware) vs. MPC's (cryptography). Tesseract also includes a dark pool mode making it directly comparable to the Bristol papers.
Read Prime Match (Polychroniadou et al., USENIX 2023). This describes a live system, not a prototype. Pay attention to what was abandoned (FHE, CDA, price discovery) and why. The academic-to-production gap is the most important lesson in this literature.
Then read Atlas-X (AAMAS 2024) to see how DP layers on top of MPC in the same production environment.
Read Buterin et al., SSRN 2023 (Privacy Pools). This introduces association sets as the key conceptual tool: "prove membership in a clean set without revealing which member you are." The framing — privacy-as-innocence-proof — is distinct from all other approaches.
Context: Tornado Cash sanctions (Aug 2022) are the real-world trigger. Privacy Pools is the answer to: "What would a regulation-compatible Tornado Cash look like?"
Read PEReDi (Kiayias, Kohlweiss et al., CCS 2022) for the regulated CBDC template. Then read PPB (Eurocrypt 2023) for the formal design language. These two papers establish the Edinburgh/IOG line that all CBDC privacy papers reference.
Read Bulletproofs (Bünz et al., S&P 2018) for the core range proof primitive. Then read Zether (FC 2020) for the Ethereum account-model application. This gives you the ZK vocabulary needed to understand colzkSNARKs (Renegade) and Atlas-X's ZK component.
Read DP-CFMM (Chitra, Angeris, Evans, FC 2022) last among foundational papers. This is the theoretical bridge between differential privacy and AMM/DEX mechanics. Understand the LP-strategy-leakage observation before reading Atlas-X's DP component.
If you can only read one researcher's full output: read Polychroniadou. The JPM line (2020→2023→2024) traces the complete arc from prototype to production. Every design decision that was made or abandoned is documented in those papers. It is the only line in DeFi privacy research with a validated ground truth: the system runs live.
If you are primarily a cryptographer: start with Smart (MP-SPDZ foundations) then Bünz (ZK). If you are a DeFi economist: start with Daian (MEV threat model) then Chitra (DP-CFMM). If you are a policy/compliance researcher: start with Buterin (Privacy Pools) then Kiayias (CBDC line).