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Deductive policies with XACML

Published: 13 November 2009 Publication History

Abstract

SaaS technology might comprise of a bundle of different services provided by different entities. Thus monolithic access policies are not feasible as each of the service partners and the companies using the service would have to provide their internal and potentially confidential rules on which they base their policies. In addition internal information such as concrete position of the user or affiliation to a specific project might be utilized in the policies and should not be provided to any external entity.
Deduction of decisions has been investigated for more than a decade, but no widely spread standard has been defined, so far. OASIS XACML is being used in many applications and services nowadays. Additionally, tools for modeling the policies are available and many engineers share common understanding of this approach. In this paper we present an extension of the XACML language to support deduction of decisions, together with a distributed definition of the policies and at the same time avoiding problems known from current solutions on deductive policy languages.

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Cited By

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  • (2022)ANNPDP: An Efficient and Stable Evaluation Engine for Large-Scale Policy SetsIEEE Transactions on Services Computing10.1109/TSC.2020.302613815:4(1926-1939)Online publication date: 1-Jul-2022
  • (2022)Policychain: A Decentralized Authorization Service With Script-Driven Policy on Blockchain for Internet of ThingsIEEE Internet of Things Journal10.1109/JIOT.2021.31091479:7(5391-5409)Online publication date: 1-Apr-2022
  • (2022)An efficient density peak cluster algorithm for improving policy evaluation performanceScientific Reports10.1038/s41598-022-08637-812:1Online publication date: 23-Mar-2022
  • Show More Cited By

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Published In

cover image ACM Conferences
SWS '09: Proceedings of the 2009 ACM workshop on Secure web services
November 2009
70 pages
ISBN:9781605587899
DOI:10.1145/1655121
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 13 November 2009

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Author Tags

  1. deduction
  2. xacml

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Cited By

View all
  • (2022)ANNPDP: An Efficient and Stable Evaluation Engine for Large-Scale Policy SetsIEEE Transactions on Services Computing10.1109/TSC.2020.302613815:4(1926-1939)Online publication date: 1-Jul-2022
  • (2022)Policychain: A Decentralized Authorization Service With Script-Driven Policy on Blockchain for Internet of ThingsIEEE Internet of Things Journal10.1109/JIOT.2021.31091479:7(5391-5409)Online publication date: 1-Apr-2022
  • (2022)An efficient density peak cluster algorithm for improving policy evaluation performanceScientific Reports10.1038/s41598-022-08637-812:1Online publication date: 23-Mar-2022
  • (2015)Managing XACML systems in distributed environments through Meta-PoliciesComputers and Security10.1016/j.cose.2014.10.00448:C(92-115)Online publication date: 1-Feb-2015
  • (2013)Federated Authorization for Software-as-a-Service ApplicationsOn the Move to Meaningful Internet Systems: OTM 2013 Conferences10.1007/978-3-642-41030-7_25(342-359)Online publication date: 2013
  • (2013)Authorization Language for Inter‐EnterpriseEnterprise Interoperability10.1002/9781118561942.ch16(103-109)Online publication date: 21-Jan-2013

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