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A Context-Aware Mandatory Access Control Model for Multilevel Security Environments

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Computer Safety, Reliability, and Security (SAFECOMP 2008)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 5219))

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Abstract

Mandatory access control models have traditionally been employed as a robust security mechanism in multilevel security environments like military domains. In traditional mandatory models, the security classes associated with entities are context-insensitive. However, context-sensitivity of security classes may be required in some environments. Moreover, as computing technology becomes more pervasive, flexible access control mechanisms are needed. Unlike traditional approaches for access control, such access decisions depend on the combination of the required credentials of users and the context of the system. Incorporating context-awareness into mandatory access control models results in a model appropriate for handling such context-aware policies and context- sensitive class association mostly needed in multilevel security environments. In this paper, we introduce a context-aware mandatory access control model (CAMAC) capable of dynamic adaptation of access control policies to the context, and handling context-sensitive class association, in addition to preservation of confidentiality and integrity. One of the most significant characteristics of the model is its high expressiveness which allows us to express various mandatory access control models such as Bell-LaPadula, Biba, Dion, and Chinese Wall with it.

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Jafarian, J.H., Amini, M., Jalili, R. (2008). A Context-Aware Mandatory Access Control Model for Multilevel Security Environments. In: Harrison, M.D., Sujan, MA. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2008. Lecture Notes in Computer Science, vol 5219. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87698-4_33

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  • DOI: https://doi.org/10.1007/978-3-540-87698-4_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87697-7

  • Online ISBN: 978-3-540-87698-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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