Secure Multi-Party Computation

Definition ∞ Secure Multi-Party Computation (SMC) is a cryptographic protocol that allows multiple parties to jointly compute a function over their private inputs without revealing those inputs to each other. This technology ensures data privacy while enabling collaborative data processing or decision-making. SMC protects sensitive information by distributing computation across several participants. It offers a powerful tool for privacy-preserving operations in decentralized environments.
Context ∞ SMC is gaining significant attention in the blockchain space as a solution for enhancing privacy and trust in decentralized applications. News reports may discuss its application in confidential transactions, private voting systems, or cross-chain interoperability where sensitive data must remain hidden. The adoption of SMC protocols addresses key privacy concerns and expands the potential for secure collaborative endeavors within the digital asset ecosystem.

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→Secure Multi-Party Computation

→Security Proofs

→Batch Auctions

Batch Processing Eliminates MEV in Automated Market Makers

This research introduces a novel batch-processing mechanism for Automated Market Makers, fundamentally mitigating Miner Extractable Value and fostering equitable transaction execution.

A sleek, translucent blue hardware wallet device rests on a dark grey surface. Its modular, clear blue-tinted casing suggests a secure element for cryptographic key storage. A prominent raised section on the left likely functions as a secure input for seed phrase entry or multi-signature confirmation. On the right, a black knob with a white top controls firmware updates or device settings. This tamper-proof unit is engineered for cold storage, facilitating offline transaction signing and safeguarding digital assets within a distributed ledger technology ecosystem.

→Randomness Generation

→Cryptographic Schemes

→Protocol Integration

Thetacrypt: Simplifying Threshold Cryptography for Distributed Systems

Thetacrypt introduces a versatile library for integrating diverse threshold cryptographic schemes, enabling simpler construction of robust, distributed systems and enhancing blockchain security.

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→Distributed Machine Learning

→Federated Learning

→AI Privacy

GuardianMPC: Backdoor-Resilient Neural Network Computation via Secure MPC

A novel framework leverages secure multi-party computation to protect neural networks from backdoor attacks, ensuring private, robust AI inference and training.

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→Three-Party Computation

→Verifiable Computation

→Off-Chain Computation

Updatable Distributed Point Functions Enable Private Account-Based Digital Currencies

UVDPF, a new cryptographic primitive, enables private, mutable state in decentralized systems, challenging the UTXO model for scalable, private digital currencies.

Translucent blue, intricately structured modules are displayed, possibly representing cryptographic primitives or smart contract logic within a decentralized ledger technology DLT framework. These interconnected elements, covered in fine droplets, suggest active data immutability and network consensus processes. A prominent metallic component, resembling a hardware security module HSM or validator node hardware, anchors the system, emphasizing robust digital asset protection and transaction finality. This visual metaphor illustrates the complex interplay of blockchain architecture and security protocols in a Proof-of-Stake PoS environment.

→Adaptive Share Delay

→Byzantine Agreement

→Communication Efficiency

Efficient Byzantine Verifiable Secret Sharing Secures Decentralized Systems Foundationally

EByFTVeS introduces an Adaptive Share Delay Provision strategy to resolve consistency and efficiency burdens in BFT-based Verifiable Secret Sharing, strengthening core cryptographic primitives.

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→Communication Overhead Reduction

→Cryptographic Primitive

→Vector Oblivious Linear Evaluation

Committed VOLE Enables Consistent Private Computation across Multiple Parties

C-VOLE is a new cryptographic primitive that ensures input consistency across multiple private computations, fundamentally accelerating secure multi-party protocols.

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→Arithmetic Circuits

→Ring-Based Cryptography

→Malicious Security

Vector-OLE Enables Efficient Zero-Knowledge Proofs over Integer Rings

A new Vector-OLE protocol provides maliciously secure, high-speed Zero-Knowledge Proofs over the integer ring $mathbb{Z}_{2^k}$, fundamentally aligning verifiable computation with modern CPU arithmetic.

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→Formal Verification

→Protocol Correctness

→Hyperproperty Preservation

Formal Compiler Proof Secures Distributed Cryptographic Applications Synthesis

A new compiler security proof unifies four formalisms to automatically synthesize complex, secure distributed protocols from simple sequential programs, guaranteeing end-to-end security.

Intricate blue and white geometric structures form a complex, interconnected system. A central, polished blue component with nested square patterns suggests a core processing unit. Surrounding translucent, crystalline elements extend into a blurred background, hinting at a vast network. This visual metaphor illustrates a decentralized ledger architecture, emphasizing the precision of cryptographic hashing and the transparent flow of transaction data within a peer-to-peer network powered by a consensus mechanism. The glowing blue signifies active block validation.

→Privacy Preserving Systems

→Private Mechanism Design

→Verifiable Compliance

Cryptographic Zk-Agreements Establish Private Deterministic Trust on Blockchains

The zk-agreements protocol uses Zero-Knowledge Proofs and MPC to finally secure confidential legal contracts on public ledgers, unlocking enterprise adoption.