Coupling of Inference and Access Controls to Ensure Privacy Protection
| Autor: | Siham Benhaddou, Anas Abou El Kalam, Jean-Philippe Leroy, Jihane El Mokhtari |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | International Journal of Safety and Security Engineering. 11:529-535 |
| ISSN: | 2041-904X 2041-9031 |
| DOI: | 10.18280/ijsse.110504 |
| Popis: | This article is devoted to the topic of coupling access and inference controls into security policies. The coupling of these two mechanisms is necessary to strengthen the protection of the privacy of complex systems users. Although the PrivOrBAC access control model covers several privacy protection requirements, the risk of inferring sensitive data may exist. Indeed, the accumulation of several pieces of data to which access is authorized can create an inference. This work proposes an inference control mechanism implemented through multidimensional analysis. This analysis will take into account several elements such as the history of access to the data that may create an inference, as well as their influence on the inference. The idea is that this mechanism delivers metrics that reflect the level of risk. These measures will be considered in the access control rules and will participate in the refusal or authorization decision with or without obligation. This is how the coupling of access and inference controls will be applied. The implementation of this coupling will be done via the multidimensional OLAP databases which will be requested by the Policy Information Point, the gateway brick of XACML to the various external data sources, which will route the inference measurements to the decision-making point. |
| Databáze: | OpenAIRE |
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