Date of Award

5-2018

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science

Committee Chair

Elisa Bertino

Committee Member 1

Walid Aref

Committee Member 2

Sonia Fahmy

Committee Member 3

Ning

Abstract

In bring-your-own-device (BYOD) and corporate-owned, personally enabled (COPE) scenarios, employees’ devices store both enterprise and personal data, and have the ability to remotely access a secure enterprise network. While mobile devices enable users to access such resources in a pervasive manner, it also increases the risk of breaches for sensitive enterprise data as users may access the resources under insecure circumstances. That is, access authorizations may depend on the context in which the resources are accessed. In both scenarios, it is vital that the security of accessible enterprise content is preserved. In this work, we explore the use of contextual information to influence access control decisions within context-aware systems to ensure the security of sensitive enterprise data. We propose several context-aware systems that rely on a system of sensors in order to automatically adapt access to resources based on the security of users’ contexts. We investigate various types of mobile devices with varying embedded sensors, and leverage these technologies to extract contextual information from the environment. As a direct consequence, the technologies utilized determine the types of contextual access control policies that the context-aware systems are able to support and enforce. Specifically, the work proposes the use of devices pervaded in enterprise environments such as smartphones or WiFi access points to authenticate user positional information within indoor environments as well as user identities.

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