AS5: A secure searchable secret sharing scheme for privacy preserving database outsourcing

Hadavi, M. A ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1007/978-3-642-35890-6_15
  3. Publisher: 2013
  4. Abstract:
  5. Researchers have been studying security challenges of database outsourcing for almost a decade. Privacy of outsourced data is one of the main challenges when the "Database As a Service" model is adopted in the service oriented trend of the cloud computing paradigm. This is due to the insecurity of the network environment or even the untrustworthiness of the service providers. This paper proposes a method to preserve privacy of outsourced data based on Shamir's secret sharing scheme. We split attribute values into several parts and distribute them among untrusted servers. The problem of using secret sharing in data outsourcing scenario is how to search efficiently within the randomly generated pool of shares. In this paper, at first, we customize Shamir's scheme to have A Searchable Secret Sharing Scheme (AS4) that enables the efficient execution of different kinds of queries over distributed shares. Then, we extend our method for sharing values to A Secure Searchable Secret Sharing Scheme (AS5) to tolerate statistical attacks based on adversary's knowledge about outsourced data distribution. In AS5 data shares are generated uniformly across a domain to prevent information leakage about the outsourced data
  6. Keywords:
  7. Secure database outsourcing ; Attribute values ; Computing paradigm ; Data confidentiality ; Data distribution ; Data outsourcing ; Data share ; Database as a service ; Network environments ; Prevent information leakage ; Privacy preserving ; Secret sharing ; Secret sharing schemes ; Secure database ; Security challenges ; Service Oriented ; Service provider ; Statistical attacks ; Untrusted server ; Database systems ; Information theory ; Outsourcing ; Query processing ; Data privacy
  8. Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Pisa ; Volume 7731 LNCS , 2013 , Pages 201-216 ; 03029743 (ISSN) ; 9783642358890 (ISBN)
  9. URL: http://link.springer.com/chapter/10.1007%2F978-3-642-35890-6_15