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Novel Threshold Changeable Secret Sharing Schemes Based on Polynomial Interpolation.
Yuan, Lifeng; Li, Mingchu; Guo, Cheng; Choo, Kim-Kwang Raymond; Ren, Yizhi.
Afiliação
  • Yuan L; School of Software Technology, Dalian University of Technology, Dalian, 116620, China.
  • Li M; Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian, 116620, China.
  • Guo C; School of Software Technology, Dalian University of Technology, Dalian, 116620, China.
  • Choo KR; Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian, 116620, China.
  • Ren Y; School of Software Technology, Dalian University of Technology, Dalian, 116620, China.
PLoS One ; 11(10): e0165512, 2016.
Article em En | MEDLINE | ID: mdl-27792784
ABSTRACT
After any distribution of secret sharing shadows in a threshold changeable secret sharing scheme, the threshold may need to be adjusted to deal with changes in the security policy and adversary structure. For example, when employees leave the organization, it is not realistic to expect departing employees to ensure the security of their secret shadows. Therefore, in 2012, Zhang et al. proposed (t → t', n) and ({t1, t2,⋯, tN}, n) threshold changeable secret sharing schemes. However, their schemes suffer from a number of limitations such as strict limit on the threshold values, large storage space requirement for secret shadows, and significant computation for constructing and recovering polynomials. To address these limitations, we propose two improved dealer-free threshold changeable secret sharing schemes. In our schemes, we construct polynomials to update secret shadows, and use two-variable one-way function to resist collusion attacks and secure the information stored by the combiner. We then demonstrate our schemes can adjust the threshold safely.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Segurança Computacional / Modelos Teóricos Tipo de estudo: Prognostic_studies Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Segurança Computacional / Modelos Teóricos Tipo de estudo: Prognostic_studies Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: China