A privacy policy conflict detection method for multi-owner privacy data protection

  • Authors:
  • Yi Ren;Fangquan Cheng;Zhiyong Peng;Xiaoting Huang;Wei Song

  • Affiliations:
  • The State-Key Lab. of Software Engineering, Wuhan University, WuHan, China and Network Management Center, Communication and Commanding Academy, WuHan, China 430010;The Computer School, Wuhan University, WuHan, China;The Computer School, Wuhan University, WuHan, China;The Computer School, Wuhan University, WuHan, China;The Computer School, Wuhan University, WuHan, China

  • Venue:
  • Electronic Commerce Research
  • Year:
  • 2011

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Abstract

The current privacy-preserving researches focus on single-owner privacy data. However, multi-owner privacy data, which is also a widespread privacy data, need to be properly protected. At first, the characteristics of multi-owner privacy data and its protection requirement is introduced in this paper. Secondly, a data schema based on deputy mechanism for multi-owner privacy data is proposed. Thirdly, based on the schema, this paper proposes a privacy policy conflict detection method based on sub-graph isomorphic. This method models the privacy policy and each possible policy conflict pattern as a stratified-directed graph (SDG), and provides an algorithm to detect whether the SDG of a privacy conflict mode is isomorphic to that of privacy policies.