Multi-secret Sharing Scheme for Level-Ordered Access Structures

Tentu, Appala Naidu; Basit, Abdul; Bhavani, K.; Venkaiah, V. Ch.

doi:10.1007/978-3-319-76620-1_16

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…Recently, there were some research studies on the compartmented access structure [17][18][19]. Tassa et al proposed two types of the compartmented secret sharing schemes based on the bivariate Lagrange interpolation [20].…”

Section: Related Workmentioning

confidence: 99%

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An Efficient Compartmented Secret Sharing Scheme Based on Linear Homogeneous Recurrence Relations

Yuan

et al. 2021

Security and Communication Networks

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Multipartite secret sharing schemes are those that have multipartite access structures. The set of the participants in those schemes is divided into several parts, and all the participants in the same part play the equivalent role. One type of such access structure is the compartmented access structure, and the other is the hierarchical access structure. We propose an efficient compartmented multisecret sharing scheme based on the linear homogeneous recurrence (LHR) relations. In the construction phase, the shared secrets are hidden in some terms of the linear homogeneous recurrence sequence. In the recovery phase, the shared secrets are obtained by solving those terms in which the shared secrets are hidden. When the global threshold is t , our scheme can reduce the computational complexity of the compartmented secret sharing schemes from the exponential time to polynomial time. The security of the proposed scheme is based on Shamir’s threshold scheme, i.e., our scheme is perfect and ideal. Moreover, it is efficient to share the multisecret and to change the shared secrets in the proposed scheme.

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Section: Related Workmentioning

confidence: 99%

“…(2) Secondly, the polynomial f 2 is recovered by P 21 , P 23 , and P 24 . For the three points (7,17), (9,9), and (10,8), a polynomial can be determined by…”

Section: Recovery Phasementioning

confidence: 99%