commitment scheme design

This study addresses the inherent tension between user privacy—encompassing anonymity, confidentiality, and unlinkability—and regulatory compliance—particularly auditability—in privacy-enhancing digital currencies, including cryptocurrencies and central bank digital currencies (CBDCs). Method: We propose a design-oriented privacy analysis framework, formalizing three generations of evolutionary models that systematically map privacy objectives to cryptographic primitives (e.g., zero-knowledge proofs, ring signatures, homomorphic encryption), protocol mechanisms, and system architectures. Our analysis draws on a horizontal comparison of over 120 privacy-preserving schemes. Contribution/Results: We identify three critical technical bottlenecks: cryptographic construction limitations, consensus mechanism constraints, and inadequate regulatory interface design. The framework yields a practical, implementable technology roadmap for next-generation CBDCs—informing system design, policy formulation, and international standardization efforts aimed at reconciling privacy protection with lawful oversight.

Traditional commit-reveal schemes are vulnerable to the “last-revealer attack,” wherein malicious participants delay revealing their commitments to bias the resulting randomness—compromising security in validator elections, zero-knowledge proof generation, and DeFi applications. To address this, we propose a two-layer commit-reveal protocol: the first layer collects commitments and randomizes the revelation order; the second layer generates the final randomness deterministically from the ordered revelations. We integrate lightweight offline P2P coordination to minimize network overhead. Our design is the first to systematically eliminate the last-revealer attack surface. A prototype implementation demonstrates a 37% reduction in communication cost compared to baseline schemes, exhibits Byzantine fault tolerance, and maintains compatibility with mainstream blockchain platforms. The reference implementation is open-sourced.

This work addresses the frequent disconnect between the mathematical certainty of numerical values in cryptographic protocols and their concrete representations, which undermines interoperability and formal verification. Drawing from representation theory, the paper introduces three classes of representations—algorithmically approximable, finitely precisely describable, and canonically normalizable—and proves that no universal computable canonicalizer can transform arbitrary approximate programs into a unique finite encoding. It extends the canonical encoding paradigm of the rational number system Σ_Q to practical cryptographic objects. By integrating computability theory with canonical serialization techniques, the approach is applied to symmetric and asymmetric encryption, hashing, and blockchain integrity protocols. Case studies such as Snaproot demonstrate that canonical representations are essential for achieving precise protocol specifications, ensuring interoperability, and enabling byte-level correctness arguments.

This work addresses the challenge of verifiable and persistent identity for autonomous software agents on public blockchains by introducing a novel paradigm that anchors agent identity in cryptographic assumptions. It deterministically derives neural network weights from private keys and employs zero-knowledge proofs at every state transition to verify the binding among the key, model, and interaction history, thereby ensuring inseparability between identity and economic stake. The proposed framework establishes, for the first time, a cryptographic invariant–based agent identity primitive on-chain and incorporates a protocol-level metabolic cost mechanism. Experimental validation on the Solana testnet over 2.36 continuous days confirmed that all state transitions were correctly verified: agents sharing the same private key exhibited consistent behavior, those with distinct keys diverged meaningfully, and unauthorized model substitutions were rejected on-chain.

This paper addresses the inherent tension between transaction transparency and user privacy in public blockchains by proposing a trustless on-chain privacy-preserving transaction scheme. Methodologically, it designs a privacy architecture integrating Twisted ElGamal elliptic-curve commitments with EC Diffie-Hellman key exchange, and employs zk-SNARKs to enable publicly verifiable encryption, decryption, and commitment procedures. The core contribution is the construction of cWETH—a composable, Ethereum-compatible privacy-preserving wrapped asset—that achieves end-to-end hiding of transaction amounts and participant identities on a fully transparent ledger, while preserving public verifiability of transaction validity. Experimental evaluation demonstrates that the scheme significantly enhances the practicality and security of on-chain private transactions without compromising decentralization or composability.

This work addresses the challenge of enabling efficient, trustless off-chain double-spending prevention while preserving privacy for both users and service providers. To this end, the authors propose a modular off-chain execution layer that leverages a public-key-based token ownership model combined with a novel multi-public-key signature scheme. This design supports stable identities and transaction unlinkability while minimizing key management overhead. Through a formal security model, the system is proven to satisfy three core properties: double-spending resistance, censorship resistance (non-blocking), and bidirectional privacy. Notably, this is the first construction to achieve a private off-chain payment mechanism that simultaneously offers high efficiency and rigorous security guarantees under a general cryptographic setting.

This work addresses the vulnerability of encrypted mempools to economically lagging and security risks arising from self-authorized state manipulation—such as perpetual contract funding rate manipulation—due to their inability to inject corrective transactions into already committed batches, despite offering protection against victim-dependent MEV attacks. The paper proposes a micro-correction mechanism grounded in executable arbitrage, modeling how correctors optimally choose order sizes balancing price impact and inventory costs, while evaluating exploitable opportunities through the lens of protocol disclosure timing. It introduces a novel local security index incorporating attacker blind spots, correction shielding, and capitalization shielding, revealing how private transactions suppress predictive capitalization of funding rates and induce dual amplification effects. By integrating game theory, market mechanism design, and encrypted mempool architecture, the study establishes a dynamic security framework driven by information scheduling and response factors, proving that closed-phase correction rates fall below adaptive correction rates and quantifying both state distortion and its responsive amplification.

This work addresses the challenge of enabling secure and programmable spending conditions without relying on consensus participants. To this end, we introduce, for the first time, a predicate mechanism into the Unicity model, extending token ownership to programmable spending predicates executed off-chain by dependent parties. This extension preserves the original system’s security guarantees while supporting off-chain smart contract functionality. Leveraging the unforgeability of predicate families, we construct a formally secure spending model and design a complementary off-chain execution architecture together with an atomic swap protocol. Our approach successfully realizes trustless atomic swaps, demonstrating the practical applicability of the proposed framework.

This work addresses the insufficient security of fiat-denominated lending protocols that use cryptocurrencies (e.g., Bitcoin) as collateral. We propose the first decentralized lending framework based on the limited-custody paradigm, relying solely on a trusted arbitration mechanism. Integrating cryptographic protocol design with game-theoretic modeling, we formally characterize participants’ strategic behaviors and prove Nash equilibrium security under rationality assumptions. Theoretical analysis demonstrates resilience against collateral price volatility and malicious collusion attacks, enabling trust-minimized collateralized loan execution. Our framework provides a provably secure foundation for integrating crypto-assets into mainstream finance and establishes a novel DeFi design paradigm—“lightweight custody + game-theoretic guarantees”—that balances security, efficiency, and decentralization.

This work addresses a critical yet overlooked class of vulnerabilities in cryptographic systems arising from the lack of a unique mapping between semantic objects and their byte representations, which can undermine mechanisms such as hashing, digital signatures, and replay protection due to representation inconsistencies. The paper presents the first systematic classification of these “representation divergence” vulnerabilities and introduces a unified framework that identifies two root causes: object-side multiple representations and encoding-side semantic collapse. By integrating formal modeling, field-type categorization, and operational boundary analysis, the authors develop an actionable canonicalization obligation review process. This approach transcends specific system implementations, establishing a general taxonomy grounded in representation mechanisms, bridging classical canonicalization security with computability theory, and demonstrating its efficacy and applicability through multiple real-world case studies.

This work addresses the challenge of achieving transaction privacy on Algorand—a high-throughput public blockchain—where smart contracts face severe resource constraints and lack global state-based concurrency control. The authors propose a decentralized, non-custodial privacy protocol that leverages LSAG ring signatures with on-chain verification to ensure anonymity. Innovatively, they replace the conventional global Merkle accumulator with an O(1) commitment membership check based on Box Storage. To overcome opcode budget limitations, an embedded application call pool is introduced for dynamic budget expansion, enabling, for the first time on Algorand, efficient signature-obfuscating privacy without trusted setup. By integrating BN254-based cryptography with lightweight on-chain verification, the protocol delivers strong privacy guarantees and selective auditability while preserving Algorand’s high throughput, all without relying on zk-SNARKs or trusted setup assumptions.