Automated policy combination for data sharing across multiple organizations

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

doi:10.1109/SCC.2015.39

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 proceeding › Conference proceeding contribution › peer-review

4 Citations (Scopus)

Abstract

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 language	English
Title of host publication	Proceedings - 2015 IEEE International Conference on Services Computing
Subtitle of host publication	SCC 2015
Editors	Paul P. Maglio, Incheon Paik, Wu Chou
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	226-233
Number of pages	8
ISBN (Electronic)	9781467372817, 9781467372800
ISBN (Print)	9781467372824
DOIs	https://doi.org/10.1109/SCC.2015.39
Publication status	Published - 17 Aug 2015
Externally published	Yes
Event	IEEE International Conference on Services Computing, SCC 2015 - New York, United States Duration: 27 Jun 2015 → 2 Jul 2015

Other

Other	IEEE International Conference on Services Computing, SCC 2015
Country/Territory	United States
City	New York
Period	27/06/15 → 2/07/15

Keywords

Data Sharing
Policy Combination
Rule Combination Algorithm

Access to Document

10.1109/SCC.2015.39

Cite this

Duan, L., Chen, S., Zhang, Y., Liu, C., Liu, D., Liu, R. P., & Chen, J. (2015). Automated policy combination for data sharing across multiple organizations. In P. P. Maglio, I. Paik, & W. Chou (Eds.), Proceedings - 2015 IEEE International Conference on Services Computing: SCC 2015 (pp. 226-233). Article 7207357 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/SCC.2015.39

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title = "Automated policy combination for data sharing across multiple organizations",

abstract = "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.",

keywords = "Data Sharing, Policy Combination, Rule Combination Algorithm",

author = "Li Duan and Shiping Chen and Yang Zhang and Chunhong Liu and Dongxi Liu and Liu, {Ren Ping} and Junliang Chen",

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booktitle = "Proceedings - 2015 IEEE International Conference on Services Computing",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

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note = "IEEE International Conference on Services Computing, SCC 2015 ; Conference date: 27-06-2015 Through 02-07-2015",

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Duan, L, Chen, S, Zhang, Y, Liu, C, Liu, D, Liu, RP & Chen, J 2015, Automated policy combination for data sharing across multiple organizations. in PP Maglio, I Paik & W Chou (eds), Proceedings - 2015 IEEE International Conference on Services Computing: SCC 2015., 7207357, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 226-233, IEEE International Conference on Services Computing, SCC 2015, New York, United States, 27/06/15. https://doi.org/10.1109/SCC.2015.39

Automated policy combination for data sharing across multiple organizations. / Duan, Li; Chen, Shiping; Zhang, Yang et al.
Proceedings - 2015 IEEE International Conference on Services Computing: SCC 2015. ed. / Paul P. Maglio; Incheon Paik; Wu Chou. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2015. p. 226-233 7207357.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Automated policy combination for data sharing across multiple organizations

AU - Duan, Li

AU - Chen, Shiping

AU - Zhang, Yang

AU - Liu, Chunhong

AU - Liu, Dongxi

AU - Liu, Ren Ping

AU - Chen, Junliang

PY - 2015/8/17

Y1 - 2015/8/17

N2 - 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.

AB - 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.

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KW - Policy Combination

KW - Rule Combination Algorithm

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Duan L, Chen S, Zhang Y, Liu C, Liu D, Liu RP et al. Automated policy combination for data sharing across multiple organizations. In Maglio PP, Paik I, Chou W, editors, Proceedings - 2015 IEEE International Conference on Services Computing: SCC 2015. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2015. p. 226-233. 7207357 doi: 10.1109/SCC.2015.39

Automated policy combination for data sharing across multiple organizations

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