ARPA Whitepaper

We propose a secure computation solution for blockchain networks. The correctness of computation is verifiable even under malicious majority condition using information-theoretic Message Authentication Code (MAC), and the privacy is preserved using Secret-Sharing. With state-of-the-art multiparty computation protocol and a layer2 solution, our privacy-preserving computation guarantees data security on blockchain, cryptographically, while reducing the heavy-lifting computation job to a few nodes. This breakthrough has several implications on the future of decentralized networks. First, secure computation can be used to support Private Smart Contracts, where consensus is reached without exposing the information in the public contract. Second, it enables data to be shared and used in trustless network, without disclosing the raw data during data-at-use, where data ownership and data usage is safely separated. Last but not least, computation and verification processes are separated, which can be perceived as computational sharding, this effectively makes the transaction processing speed linear to the number of participating nodes. Our objective is to deploy our secure computation network as an layer2 solution to any blockchain system. Smart Contracts\cite{smartcontract} will be used as bridge to link the blockchain and computation networks. Additionally, they will be used as verifier to ensure that outsourced computation is completed correctly. In order to achieve this, we first develop a general MPC network with advanced features, such as: 1) Secure Computation, 2) Off-chain Computation, 3) Verifiable Computation, and 4)Support dApps’ needs like privacy-preserving data exchange.

💡 Research Summary

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The ARPA whitepaper presents a comprehensive layer‑2 solution that brings secure multiparty computation (MPC) to existing blockchain ecosystems while preserving privacy and achieving linear scalability. The authors identify two fundamental shortcomings of current blockchains: (1) on‑chain computation is limited by gas caps, leading to high transaction fees and limited throughput, and (2) all data processed on‑chain is publicly visible, which defeats the privacy expectations of many real‑world applications. To address these issues, ARPA proposes to move the heavy computational work off‑chain, verify the results on‑chain, and use smart contracts as the bridge and verifier.

The core cryptographic building blocks are information‑theoretic Message Authentication Codes (MAC) and Shamir‑based secret sharing. During the off‑chain phase, participating nodes receive secret‑shared inputs, evaluate the Boolean/arithmetic circuit gate‑by‑gate, and update a MAC that authenticates the intermediate state. At the end of the computation, the final output together with the final MAC is submitted to a smart contract. Because MAC verification is O(1) in gas, the on‑chain verification cost is negligible, allowing the verification step to be performed by any node without risking a denial‑of‑service attack. This design guarantees correctness even under a malicious‑majority adversary: any colluding subset of nodes cannot forge a valid MAC without being detected.

The protocol is split into a preprocessing stage (function compilation, circuit generation, secret‑share and MAC key distribution) and an execution stage (share exchange, circuit evaluation, MAC update, result reveal). The preprocessing is performed once per function, enabling reuse across many executions. The execution stage is fully parallelizable across the participating nodes, and because verification does not depend on the circuit size, the overall transaction throughput scales linearly with the number of computation nodes—a property the authors refer to as “computational sharding”.

ARPA’s system architecture includes an ARPA Virtual Machine (A‑VM) that runs the compiled circuits, an interoperability layer that connects to any EVM‑compatible blockchain, and a set of smart contracts that manage job submission, node selection, staking, and result verification. Node selection combines a lottery‑style random draw with a stake‑based reputation system, mitigating Sybil attacks and encouraging honest participation. The token economics are designed to reward computation nodes, data providers, and model providers, while penalizing malicious behavior through slashing of staked tokens. The authors also model bribery attacks and demonstrate that the MAC‑based verification makes it economically infeasible for an attacker to corrupt a majority of nodes without incurring prohibitive costs.

In the background section, the paper contrasts ARPA’s MPC approach with three other families of secure computation: homomorphic encryption (HE), zero‑knowledge proofs (ZKP/zk‑SNARK), and trusted execution environments (TEE). HE offers strong confidentiality but suffers from massive ciphertext expansion and prohibitive bootstrapping costs, making it unsuitable for large‑scale, low‑latency applications. ZKP‑based solutions provide succinct proofs but require heavy proof generation and verification, which again inflates on‑chain costs. TEEs rely on hardware trust and are vulnerable to side‑channel attacks. By contrast, ARPA’s purely cryptographic MPC eliminates hardware trust assumptions and keeps on‑chain overhead minimal.

The experimental evaluation showcases two use cases: a Vickrey auction and a deep‑learning model training task. In both cases, ARPA achieves 5–6 orders of magnitude speedup compared with state‑of‑the‑art HE implementations while preserving exact privacy guarantees. The authors also outline a full ecosystem comprising computation nodes, data providers, data consumers, model providers, and backers, illustrating how data can be rented, processed, and monetized without ever exposing raw data.

Finally, the roadmap details milestones from prototype development, testnet deployment, integration with major blockchains (Ethereum, EOS, etc.), token launch, to a target of global production deployment by 2025. In summary, ARPA delivers a practical, cryptographically sound layer‑2 MPC platform that enables private smart contracts, secure data marketplaces, and scalable off‑chain computation, positioning it as a pivotal infrastructure for the next generation of decentralized applications.