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A Chinese wall security model for decentralized workflow systems
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Source Conference on Computer and Communications Security archive
Proceedings of the 8th ACM conference on Computer and Communications Security table of contents
Philadelphia, PA, USA
Session: Access Control table of contents
Pages: 48 - 57  
Year of Publication: 2001
ISBN:1-58113-385-5
Authors
Vijayalakshmi Atluri  Rutgers University, Newark, NJ
Soon Ae Chun  Rutgers University, Newark, NJ
Pietro Mazzoleni  Universita Di Milano, Milan, Italy
Sponsor
SIGSAC: ACM Special Interest Group on Security, Audit, and Control
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 13,   Downloads (12 Months): 70,   Citation Count: 12
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ABSTRACT

Workflow systems are gaining importance as an infrastructure for automating inter-organizational interactions, such as those in Electronic Commerce. Execution of inter-organiz-ational workflows may raise a number of security issues including those related to conflict-of-interest among competing organizations. Moreover, in such an environment, a centralized Workflow Management System is not desirable because: (i) it can be a performance bottleneck, and (ii) the systems are inherently distributed, heterogeneous and autonomous in nature. In this paper, we propose an approach to realize decentralized workflow execution, in which the workflow is divided into partitions called self-describing workflows, and handled by a light weight workflow management component, called workflow stub, located at each organizational agent. We argue that placing the task execution agents that belong to the same conflict-of-interest class in one self-describing workflow may lead to unfair, and in some cases, undesirable results, akin to being on the wrong side of the Chinese wall. We propose a Chinese wall security model for the decentralized workflow environment to resolve such problems, and a restrictive partitioning solution to enforce the proposed model.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  12

Collaborative Colleagues:
Vijayalakshmi Atluri: colleagues
Soon Ae Chun: colleagues
Pietro Mazzoleni: colleagues