2017 International Conference on Networking and Network Applications (NaNA) 2017
DOI: 10.1109/nana.2017.62
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Efficient (k, n) Secret Sharing Scheme Secure against k — 2 Cheaters

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Cited by 2 publications
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“…In this section, we review the known works for realizing verifiable secret sharing, in particular, detection and identification of malicious actions. Some methods for realizing verifiable secret sharing include the process of using additional data called an authenticator that has a specific relationship with the secret input (hereinafter referred to as the authenticator method) [5]- [8], [10]- [13], the method of detecting and correcting false shares (or errors) using Reed-Solomon code (referred to as the RS method) [14], and a method that can verify the reconstructed result using only the distributed shares (for example, Harn et al's method [20]), etc.…”
Section: Previous Work For Vssmentioning
confidence: 99%
“…In this section, we review the known works for realizing verifiable secret sharing, in particular, detection and identification of malicious actions. Some methods for realizing verifiable secret sharing include the process of using additional data called an authenticator that has a specific relationship with the secret input (hereinafter referred to as the authenticator method) [5]- [8], [10]- [13], the method of detecting and correcting false shares (or errors) using Reed-Solomon code (referred to as the RS method) [14], and a method that can verify the reconstructed result using only the distributed shares (for example, Harn et al's method [20]), etc.…”
Section: Previous Work For Vssmentioning
confidence: 99%
“…For solving the high computational complexity of HSMM, Liu et al (2012) further utilized the sequential Monte Carlo method to approximate posterior probability in training and decoding. Zhu and Liu (2017) developed a forward-only algorithm to train HSMM for online tool wear estimation. Among the research of this area, a type of 3-State HSMM with Erlang distributions of state duration, fixed state transition probability, and Mixture of Gaussians of observations, called MoG-HSMM, is widely applicable for its simplicity.…”
Section: Literature Reviewmentioning
confidence: 99%