DocumentCode :
2164157
Title :
Towards Robust and Adaptive Semantic-Based Compliance Auditing
Author :
Yip, Frederick ; Wong, Alfred Ka yiu ; Parameswaran, Nandan ; Ray, Pradeep
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of New South Wales, Sydney, NSW
fYear :
2007
fDate :
15-16 Oct. 2007
Firstpage :
181
Lastpage :
188
Abstract :
Compliance management (CM) is the management process that an organization implements to ensure organizational compliance with relevant requirements and expectations. Compliance auditing (CA) is a child-process of CM where compliance rules and policies are individually checked against the organization to determine the level of compliance achieved by the organization. In this paper, we arrange organizational knowledge and facts within OWL ontologies and model compliance rules as adaptive semantic-based rules for compliance audit automation. We study the issues of uncertainty and inconsistency in compliance and propose an adaptive human-like strategy for mimicking conventional compliance auditing.
Keywords :
auditing; ontologies (artificial intelligence); OWL ontologies; adaptive semantic-based compliance auditing; adaptive semantic-based rules; compliance management; Engineering management; ISO standards; Information management; Information security; OWL; Ontologies; Protection; Risk management; Robustness; Technology management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
EDOC Conference Workshop, 2007. EDOC '07. Eleventh International IEEE
Conference_Location :
Annapolis, MD
Electronic_ISBN :
978-0-7695-3338-4
Type :
conf
DOI :
10.1109/EDOCW.2007.33
Filename :
4566971
Link To Document :
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