Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
A Survey on Verifiable Cross-Silo Federated Learning
Authors: Aleksei Korneev, Jan Ramon
TMLR 2025 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we present a survey on verifiable cross-silo FL. We analyze various protocols, fit them in a taxonomy, and compare their efficiency and threat models. We also analyze Zero-Knowledge Proof (ZKP) schemes and discuss how their overall cost in a FL context can be minimized. Lastly, we identify research gaps and discuss potential directions for future scientific work. |
| Researcher Affiliation | Academia | Aleksei Korneev EMAIL University of Lille, Inria, CNRS, Centrale Lille, UMR 9189 CRISt AL Jan Ramon EMAIL University of Lille, Inria, CNRS, Centrale Lille, UMR 9189 CRISt AL |
| Pseudocode | Yes | Algorithm 1 Generic RA-based verification For a client Ci : Input: Private data di 1. Receive the global model θ from the server 2. Compute the local model θi using di and θ 3. Compute the ciphertext/tag ti using di and/or θi 4. Send θi and ti to the server 5. Receive the updated global model θ+ and the aggregated ciphertext/tag t from the server 6. Verify the correctness of θ+ using t For a server S : Input: Global model θ 1. Send the global model θ to each client 2. Receive ciphertexts/tags {ti}C i=1 and local models {θi}C i=1 from all clients 3. Compute the updated global model θ+ by aggregating {θi}C i=1 4. Compute the aggregated ciphertext/tag t by aggregating {ti}C i=1 5. Send θ+ and t to all clients |
| Open Source Code | No | The paper is a survey and analysis of existing verifiable cross-silo FL protocols and ZKP schemes. It does not describe a new methodology that would typically have accompanying source code. No explicit statement or link to source code is provided for the work presented in this paper. |
| Open Datasets | No | The paper is a survey and analysis of existing verifiable cross-silo FL protocols. It does not conduct its own experiments or use any specific dataset for evaluation within this paper. |
| Dataset Splits | No | The paper is a survey and analysis of existing verifiable cross-silo FL protocols. It does not conduct its own experiments or specify dataset splits. |
| Hardware Specification | No | The paper is a survey and analysis of existing verifiable cross-silo FL protocols. It does not conduct its own experiments and therefore does not specify any hardware for running them. |
| Software Dependencies | No | The paper is a survey and analysis of existing verifiable cross-silo FL protocols. It does not describe an implementation of its own methodology that would require software dependencies. |
| Experiment Setup | No | The paper is a survey and analysis of existing verifiable cross-silo FL protocols. It does not conduct its own experiments or provide details on an experimental setup. |