Wireless Sensor Networks (WSNs) have recently attracted much interest in the research community because of their wide range of applications. One emerging application for WSNs involves their use in healthcare where they are generally termed Wireless Medical Sensor Networks (WMSNs). In a hospital, fitting patients with tiny, wearable, wireless vital sign sensors would allow doctors, nurses and others to continuously monitor the state of those in their care. In the healthcare industry, patients are expected to be treated in reasonable time and any loss in data availability can result in further decline in the patient's condition or can even lead to death. Therefore, the availability of data is more important than security concerns. The overwhelming priority is to take care of the patient, but the privacy and confidentiality of that patient's medical records cannot be neglected. In current healthcare applications, there are many problems concerning security policy violations such as unauthorised denial of use, unauthorised information modification and unauthorised information release of medical data in the real world environment. Current WSN access control models used the traditional Role-Based Access Control (RBAC) or cryptographic methods for data access control but the systems still need to predefine attributes, roles and policies before deployment. It is, however, difficult to determine in advance all the possible needs for access in real world applications because there may be unanticipated situations at any time. This research proceeds to study possible approaches to address the above issues and to develop a new access control model to fill the gaps in work done by the WSN research community. Firstly, the adaptive access control model is proposed and developed based on the concept of discretionary overriding to address the data availability issue. In the healthcare industry, there are many problems concerning unauthorised information release. So, we extended the adaptive access control model with a prevention and detection mechanism to detect security policy violations, and added the concept of obligation to take a course of action when a restricted access is granted or denied. However, this approach does not consider privacy of patients' information because data availability is prioritised. To address the conflict between data availability and data privacy, this research proposed the Trust-based Adaptive Access Control (TBA2C) model that integrates the concept of trust into the previous model. A simple user behaviour trust model is developed to calculate the behaviour trust value which measures the trustworthiness of the users and that is used as one of the defined thresholds to override access policy for data availability purpose, but the framework of the TBA2C model can be adapted with other trust models in the research community. The trust model can also protect data privacy because only a user who satisfies the relevant trust threshold can get restricted access in emergency and unanticipated situations. Moreover, the introduction of trust values in the enforcement of authorisation decisions can detect abnormal data access even from authorised users. Ponder2 is used to develop the TBA2C model gradually, starting from a simple access control model to the full TBA2C. In Ponder2, a Self-Managed Cell (SMC) simulates a sensor node with the TBA2C engine inside it. Additionally, to enable a full comparison with the proposed TBA2C model, the Break-The-Glass Role Based Access Control (BTGRBAC) model is redesigned and developed in the same platform (Ponder2). The proposed TBA2C model is the first to realise a flexible access control engine and to address the conflict between data availability and data privacy by combining the concepts of discretionary overriding, the user behaviour trust model, and the prevention and detection mechanism.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:679614 |
| Date | January 2015 |
| Creators | Maw, Htoo Aung |
| Publisher | University of Hertfordshire |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/2299/16564 |
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