LaF: Lattice-Based and Communication-Efficient Federated Learning

Xu, Peng; Hu, Manqing; Chen, Tianyang; Wang, Wei; Jin, Hai

doi:10.1109/tifs.2022.3186739

Cited by 19 publications

(3 citation statements)

References 35 publications

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“…In 2022, Peng Xu et al [62] adapted the scheme, applied it to the aggregation of security models in federated learning, and constructed a post-quantum secure privacypreserving federated learning framework. We will elaborate on this part in the application of Section 7.3 In 2022, Jing Yang et al [44] proposed a computationally secure MSSS for quantum computers using inhomogeneous linear recursion (ILR) and the Ajtai function.…”

Section: Lattice-based Multi-stage Secret Sharing Schemementioning

confidence: 99%

“…However, this method is not effective against quantum attacks, and the process of computing the mask and unmasking requires a lot of communication between the parties. In order to solve the problem, Xu et al [62] proposed a post-quantum secure federated learning privacy protection framework based on Pilaram et al's scheme [41] in 2022. In each training session of federated learning, participants modify their own secret share information by updating the public parameters.…”

Section: Privacy-preserving Federated Learningmentioning

confidence: 99%

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Lattice-Based Threshold Secret Sharing Scheme and Its Applications: A Survey

Chen,

Deng,

et al. 2024

Electronics

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As the most popular cryptographic scheme in the post-quantum field, lattices have received extensive attention and research. Not only do they provide quantum-resistant security, they also enable the construction of complex applications. Currently, lattice cryptography schemes based on different difficult problems have been applied in different fields. The threshold secret sharing (TSS) scheme is an important field of cryptography and has important application value and development prospects in key protection, secure multi-party computation, privacy protection, etc. However, with the rapid development of quantum computing, many existing cryptography-underlying technologies are facing huge difficulties and challenges. Therefore, post-quantum TSS has important research significance and value for the future development of cryptography. In this paper, we summarize the existing secret sharing schemes based on lattice-hard problems and the relevant applications of these schemes in the post-quantum realm. We classify existing lattice-based TSS according to different functions and introduce typical solutions. To the best of our knowledge, this is the first review paper on lattice-based TSS schemes.

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Section: Lattice-based Multi-stage Secret Sharing Schemementioning

confidence: 99%

Section: Privacy-preserving Federated Learningmentioning

confidence: 99%

Lattice-Based Threshold Secret Sharing Scheme and Its Applications: A Survey

Chen,

Deng,

et al. 2024

Electronics

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“…SS is a technique that divides a secret into multiple parts and distributes them to different participants. The secret can only be reconstructed when specific conditions are met [53,54].…”

Section: Secret Sharingmentioning

confidence: 99%

A Privacy Robust Aggregation Method Based on Federated Learning in the IoT

Li¹,

Wang

Ren

2023

Electronics

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Federated learning has been widely applied because it enables a large number of IoT devices to conduct collaborative training while maintaining private data localization. However, the security risks and threats faced by federated learning in IoT applications are becoming increasingly prominent. Except for direct data leakage, there is also a need to face threats that attackers interpret gradients and infer private information. This paper proposes a Privacy Robust Aggregation Based on Federated Learning (PBA), which can be applied to multiple server scenarios. PBA filters outliers by using the approximate Euclidean distance calculated from binary sequences and the 3σ criterion. Then, this paper provides correctness analysis and computational complexity analysis on the aggregation process of PBA. Moreover, the performance of PBA is evaluated concerning ensuring privacy and robustness in this paper. The results indicate that PBA can resist Byzantine attacks and a state-of-the-art privacy inference, which means that PBA can ensure privacy and robustness.

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Performance analysis and evaluation of postquantum secure blockchained federated learning

Gurung,

Pokhrel,

2024

Computer Networks

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LaF: Lattice-Based and Communication-Efficient Federated Learning

Cited by 19 publications

References 35 publications

Lattice-Based Threshold Secret Sharing Scheme and Its Applications: A Survey

Lattice-Based Threshold Secret Sharing Scheme and Its Applications: A Survey

A Privacy Robust Aggregation Method Based on Federated Learning in the IoT

Performance analysis and evaluation of postquantum secure blockchained federated learning

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