Towards Robust and Adaptive Semantic-Based Compliance Auditing

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.