A Semantic Model for Personal Consent Management

Abstract

Data protection and privacy has a significant importance in information sharing mechanisms, especially in domains that handle with sensitive information. The knowledge that can be inferred from this sensitive information may unveil the consumer's personal information. Consumers should control who can access their consent data and for what purposes this data will be used. Therefore, information sharing requires effective policies to protect the personal data and to ensure the consumer's privacy needs. As different consumers have different privacy levels, each consumer should determine one's own consent policy. Besides ensuring personal privacy, information sharing to obtain personal data usage for acceptable reasons should be endorsed. This work proposes a semantic web based personal consent management model. In this model, consumers specify their consent data and create their personal consent policy for their consent data according to their privacy concerns. Thus, personalized consumer privacy for consent management will be ensured and reasonable information sharing for the personal data usage will be supported. © Springer International Publishing Switzerland 2013.