Automated policy combination for data sharing across multiple organizations

Li Duan, Shiping Chen, Yang Zhang, Chunhong Liu, Dongxi Liu, Ren Ping Liu, Junliang Chen

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

4 Citations (Scopus)


During business consolidation, multiple organizations need to share data for common interests. However, these organizations may apply different or even conflicting policies, on account of different rules and rule combining algorithms chosen by them. Thus, it is necessary to combine policies from multiple organizations into a global one to manage the access to the shared data. Existing policy combining approaches are unable to automatically combine policies into a global one. In this paper, we propose an approach to address the issue of multiple policies combination. Its key idea is to first decompose the rules in each policy into various classes, and then combine the rules of the corresponding classes to a global compact policy. The latter ensures compliance with each of the original policies at the syntax and semantic levels. To validate our approach, we provide a proof-of-concept implementation of the automated policy combination.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Services Computing
Subtitle of host publicationSCC 2015
EditorsPaul P. Maglio, Incheon Paik, Wu Chou
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Electronic)9781467372817, 9781467372800
ISBN (Print)9781467372824
Publication statusPublished - 17 Aug 2015
Externally publishedYes
EventIEEE International Conference on Services Computing, SCC 2015 - New York, United States
Duration: 27 Jun 20152 Jul 2015


OtherIEEE International Conference on Services Computing, SCC 2015
CountryUnited States
CityNew York


  • Data Sharing
  • Policy Combination
  • Rule Combination Algorithm


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