Leakage-Resilience of the Shamir Secret-Sharing Scheme Against Physical-Bit Leakages

Maji, Hemanta K.; Nguyen, Huy Hung; Paskin-Cherniavsky, Anat; Suad, Tom; Wang, Mingyuan

doi:10.1007/978-3-030-77886-6_12

Cited by 17 publications

(3 citation statements)

References 35 publications

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“…On the basis of the Chinese Remainder Theorem (CRT), Mignotte (1982) and Asmuth and Bloom (1983) introduced another two secret sharing schemes. Several researchers (Pang and Wang 2005;Steinfeld et al 2007;Maji et al 2021;Hineman and Blaum 2022) have extended the scheme proposed by Shamir (1979) using different innovative concepts. The formal definition of (t, n) -TSS scheme (Stinson and Paterson 2018) is mentioned as follows:…”

Section: Secret Sharing-based Security Solutions For Federated Learningmentioning

confidence: 99%

A multifaceted survey on privacy preservation of federated learning: progress, challenges, and opportunities

Saha,

Hota,

Chattopadhyay

et al. 2024

Artif Intell Rev

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Federated learning (FL) refers to a system of training and stabilizing local machine learning models at the global level by aggregating the learning gradients of the models. It reduces the concern of sharing the private data of participating entities for statistical analysis to be carried out at the server. It allows participating entities called clients or users to infer useful information from their raw data. As a consequence, the need to share their confidential information with any other entity or the central entity called server is eliminated. FL can be clearly interpreted as a privacy-preserving version of traditional machine learning and deep learning algorithms. However, despite this being an efficient distributed training scheme, the client’s sensitive information can still be exposed to various security threats from the shared parameters. Since data has always been a major priority for any user or organization, this article is primarily concerned with discussing the significant problems and issues relevant to the preservation of data privacy and the viability and feasibility of several proposed solutions in the FL context. In this work, we conduct a detailed study on FL, the categorization of FL, the challenges of FL, and various attacks that can be executed to disclose the users’ sensitive data used during learning. In this survey, we review and compare different privacy solutions for FL to prevent data leakage and discuss secret sharing (SS)-based security solutions for FL proposed by various researchers in concise form. We also briefly discuss quantum federated learning (QFL) and privacy-preservation techniques in QFL. In addition to these, a comparison and contrast of several survey works on FL is included in this work. We highlight the major applications based on FL. We discuss certain future directions pertaining to the open issues in the field of FL and finally conclude our work.

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Section: Secret Sharing-based Security Solutions For Federated Learningmentioning

confidence: 99%

A multifaceted survey on privacy preservation of federated learning: progress, challenges, and opportunities

Saha,

Hota,

Chattopadhyay

et al. 2024

Artif Intell Rev

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show abstract

“…Based on this state of the art, the main goal of this paper is to provide theoretical explanations for previous empirical observations on prime-field masking, in order to establish foundations on which prime ciphers could be designed. Interestingly, it turns out that the case of bit (e.g., LSB) leakages has been the topic of (for now mostly theoretical) investigations in the context of leakageresilient secret sharing, and extended towards any deterministic leakage model with a bounded range [7,27,31,8,28,30,29]. Among others, these works show that bit leakages are in some sense the most powerful leakage functions with bounded range, which therefore raises the question whether more positive results could be obtained for other, ideally more realistic, leakage functions.…”

Section: Introductionmentioning

confidence: 99%

Connecting Leakage-Resilient Secret Sharing to Practice: Scaling Trends and Physical Dependencies of Prime Field Masking

Faust,

Masure,

Micheli

et al. 2024

Lecture Notes in Computer Science

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Symmetric ciphers operating in (small or mid-size) prime fields have been shown to be promising candidates to maintain security against low-noise (or even noise-free) side-channel leakage. In order to design prime ciphers that best trade physical security and implementation efficiency, it is essential to understand how side-channel security evolves with the field size (i.e., scaling trends). Unfortunately, it has also been shown that such scaling trends depend on the leakage functions and cannot be explained by the standard metrics used to analyze Boolean masking with noise. In this work, we therefore initiate a formal study of prime field masking for two canonical leakage functions: bit leakages and Hamming weight leakages. By leveraging theoretical results from the leakage-resilient secret sharing literature, we explain formally why (1) bit leakages correspond to a worst-case and do not encourage operating in larger fields, and (2) an opposite conclusion holds for Hamming weight leakages, where increasing the prime field modulus p can contribute to a security amplification that is exponential in the number of shares, with log(p) seen as security parameter like the noise variance in Boolean masking. We combine these theoretical results with simulated experiments and show that the interest masking in larger prime fields can degrade gracefully when leakage functions slightly deviate from the Hamming weight abstraction, motivating further research towards characterizing (ideally wide) classes of leakage functions offering such guarantees.

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“…Therefore, cryptographic primitives with leakage resilience are required to meet the security requirements of the actual applications [1]. In the past fews years, the leakage-resilient cryptography has become one of the research hotspots [2], [3], and several cryptographic primitives with leakage resilience were proposed, such as identity-based encryption (IBE) [4]- [6], secret sharing [7], [8], and authenticated key exchange [9].…”

Section: Introductionmentioning

confidence: 99%

A Novel Construction of Updatable Identity-Based Hash Proof System and Its Applications

et al. 2023

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In the previous works, to further provide the continuous leakage resilience for the identity-based encryption scheme, a new cryptography primitive, called updatable identity-based hash proof system (U-IB-HPS), was proposed. However, most of the existing constructions have some deficiencies, they either do not have perfect key update function or the corresponding security with tight reduction relies on a non-static complexity assumption. To address the above problems, a new construction of U-IB-HPS is created, and the corresponding security of our system is proved based on the static complexity assumption. Also, the corresponding comparisons and analysis of performances show that our proposal not only achieves the perfect key update function and the anonymity, but also has the tight security reduction. In additional, our proposal achieves the same computational efficiency as other previous systems. To further illustrate the practical function of U-IB-HPS, a generic method of non-interactive data authorization protocol with continuous leakage resilience is designed by employing U-IB-HPS as an underlying tool, which can provide continuous leakage-resilient data authorization function for the cloud computing. Hence, the application field of U-IB-HPS is further extended through our study.

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Leakage-Resilience of the Shamir Secret-Sharing Scheme Against Physical-Bit Leakages

Cited by 17 publications

References 35 publications

A multifaceted survey on privacy preservation of federated learning: progress, challenges, and opportunities

A multifaceted survey on privacy preservation of federated learning: progress, challenges, and opportunities

Connecting Leakage-Resilient Secret Sharing to Practice: Scaling Trends and Physical Dependencies of Prime Field Masking

A Novel Construction of Updatable Identity-Based Hash Proof System and Its Applications

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