research solutions

Elevating blockchain applications with tailored solutions

We partner with industry leaders, pioneering protocols, and forward-thinking funds to elevate the potential of blockchain applications, via applied research tailored to meet the diverse needs of our clients. We enhance their solutions by leveraging the latest developments in zk-proofs, consensus protocols, and other schemes.

Decentralized identity, credentials, decentralized justice, and a quality operator set.

This is a research project that Nethermind is currently conducting on behalf of Lido.

The problem

Lido is a liquid staking protocol that converts ETH to a liquid token and stakes the funds on the Beacon Chain. It relies on external parties, called operators, for validators. Operator candidates must currently be approved by the Lido DAO through a voting process, granting the DAO a great deal of power. Ideally, the onboarding process should be permissionless without input from the DAO, while remaining as capital-efficient as possible.

The solution

As part of our collaboration with Lido, we engaged in a multi-phase research project spanning the following subjects:

Phase 1 of our project focused on systematizing knowledge for decentralized identity and verifiable credential schemes, intending to utilize these to facilitate Sybil resistance. We looked at classical results, academic research, and projects that aim to implement these primitives, with special attention given to projects from the Web3 space.

Phase 2 of our project explored the research and design considerations behind a decentralized dispute resolution mechanism for the Lido protocol, created to punish misbehaving operators. The mechanism focused on achieving white-labeling resistance—that is, preventing node operators from delegating their duties to a third party without the protocol’s knowledge, thus impeding the centralization of stake or protocol takeover by a third party. To this end, we first conducted a systematization of knowledge on decentralized justice protocols, which we leverage in our design of the dispute resolution mechanism.

Future research directions may involve further analysis and design of a Sybil-resistant mechanism, as well as utilizing reputation systems for permissionless operators and their performance.

Phase 1 results

Phase 2 results

The problem

The solution

Phase 1 of our project focused on systematizing knowledge for decentralized identity and verifiable credential schemes. We looked at classical results, academic research, and projects that aim to implement these primitives, with special attention given to projects from the Web3 space. In the following phases, we will address:

Sybil and White-label Resistance: To preserve decentralization and remove any single points of failure preventing any one operator from controlling too much staked funds is crucial. We will design a mechanism that makes it difficult for a party to onboard multiple operators without disclosing that the operators are connected, or to run the operator through a white-label operator without running the operator themselves.

Reputation system: Onboarded operators are paid for performing their duties. A reputation system is needed to trace the operators’ performance, measure how much they contribute to the quality of the operators’ set, and pay rewards accordingly.

Permissionless operators onboarding: We will design a decentralized system to permissionlessly onboard operators. The system will verify their credentials, such as who they are and whether they can perform the necessary tasks, using web3 primitives such as oracles, token-curated assets, and prediction markets.

Phase 1 results

Phase 2 results

Distributed Validator Technology (DVT)

Distributed Validator Technology (DVT) is a system that enables an Ethereum validator, responsible for proposing a block or attesting on a proposed block, to operate across multiple computers instead of just one. This approach increases security and reliability. In simple terms, if t or less computers get hacked, the attackers won't be able to sign messages or steal the validator's secret keys. Moreover, if more than t computers are functioning correctly, they can work together to perform the validator's tasks and sign transaction blocks securely. This research addresses critical aspects of security, decentralization, and reliability within the Ethereum protocol.

Our team has broad expertise on DVT building blocks such as distributed key generation (DKG), threshold signature schemes (TSSs), and consensus algorithms.

Distributed Key Generation (DKG) protocols

Allow mutually distrusting parties to jointly generate a signing key. Each party holds only a share of the key, and at least t out of n parties are needed to sign a message.

Threshold Signature Schemes (TSS)

Allow parties to perform the signing operation without revealing the secret signing key.

Consensus algorithms

Enable parties to agree on the block they will sign.

Distributed Validator Technology (DVT)

Distributed Validator Technology (DVT) is a system that enables an Ethereum validator, responsible for proposing a block or attesting on a proposed block, to operate across multiple computers instead of just one. This approach increases security and reliability. In simple terms, if t or less computers get hacked, the attackers won't be able to sign messages or steal the validator's secret keys. Moreover, if more than t computers are functioning correctly, they can work together to perform the validator's tasks and sign transaction blocks securely. This research addresses critical aspects of security, decentralization, and reliability within the Ethereum protocol.
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Our team has broad expertise on DVT building blocks such as distributed key generation (DKG), threshold signature schemes (TSSs), and consensus algorithms.

Distributed Key Generation (DKG) protocols

Allow mutually distrusting parties to jointly generate a signing key. Each party holds only a share of the key, and at least t out of n parties are needed to sign a message.

Threshold Signature Schemes (TSS)

Allow parties to perform the signing operation without revealing the secret signing key.

Consensus algorithms

Enable parties to agree on the block they will sign.

Measuring Ethereum’s client diversity

Understanding the distribution of Ethereum’s execution-layer and consensus-layer clients used by validators is vital to ensure a resilient and diverse network. Although there are currently methods toestimate the Beacon Chain’s client distribution among validators, the same cannot be said about execution client distribution. Also, there are no standard means of anonymously showcasing which EL and CL clients are being utilized by validators.

Therefore, as part of the Ethereum Foundation’s Data Collection Grants Round 2023 which ran between last September and October, an interdisciplinary team involving Nethermind Research and Nethermind core developers received a grant to work on the project “Allowing validators to provide client information privately”. This project aims to research and design a mechanism to submit and extract this crucial data while potentially avoiding compromising user anonymity and network performance.

Learn more

Collaborating on this project

Jorge

Arce-Garro

Ahmet

Ramazan Agirtas

Collaborating on this project

Jorge

Arce-Garro

Ahmet

Ramazan Agirtas

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