Privacy-preserving data analytics as an outsourced service

  • Authors:
  • Florian Kerschbaum;Julien Vayssière

  • Affiliations:
  • SAP Research, Karlsruhe, Germany;SAP Research, Brisbane, Australia

  • Venue:
  • Proceedings of the 2008 ACM workshop on Secure web services
  • Year:
  • 2008

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Abstract

Two sets of privacy requirements need to be fulfilled when a company's accounting data is audited by an external party: the company needs to safeguard its data, while the auditors do not want to reveal their investigation methods. This problem is usually addressed by physically isolating data and auditors during the course of an audit. This approach however no longer works when auditing is performed remotely. We present a searchable encryption scheme for outsourcing data analytics. In our scheme the data owner needs to encrypt his data only once and ship it in encrypted form to the data analyst. The data analyst can then perform a series of queries for which he must ask the data owner for help in translating the constants in the queries. Our searchable encryption schemes allows keyword searches and range queries. Furthermore it allows queries to reuse the results of previous queries as tokens and thereby make dependent queries without interaction. Nevertheless our scheme is provably secure.