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Performance-Aware Trust-Based Access Control for Protecting Sensitive Attributes

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Recent Advances on Soft Computing and Data Mining (SCDM 2016)

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Abstract

The prevailing trend of the seamless digital collection has prompted privacy concern not only among academia but also among the majority. In enforcing the automation of privacy policies and law, access control has been one of the most devoted subjects. Despite the recent advances in access control frameworks and models, there are still issues that impede the development of effective access control. Among them are the lack of assessment’s granularity in user authorization, and reliance on identity, role or purpose-based access control schemes. In this paper, we address the problem of protecting sensitive attributes from inappropriate access. We propose an access control mechanism that employs two trust metrics name experience and behavior. We also propose a scheme for quantifying those metrics in an enterprise computing environment. Finally, we show that these metrics are useful in improving the assessment granularity in permitting or prohibiting users to gain access to sensitive attributes.

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Acknowledgments

The authors would like to thank the reviewers for their valuable comments to help improve this article. This work is partly sponsored by the Scholarship Department, Ministry of Education, Malaysia.

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Correspondence to Mohd Rafiz Salji .

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Salji, M.R., Udzir, N.I., Ninggal, M.I.H., Sani, N.F.M., Ibrahim, H. (2017). Performance-Aware Trust-Based Access Control for Protecting Sensitive Attributes. In: Herawan, T., Ghazali, R., Nawi, N.M., Deris, M.M. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2016. Advances in Intelligent Systems and Computing, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-319-51281-5_56

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  • DOI: https://doi.org/10.1007/978-3-319-51281-5_56

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