Securing communications in vehicle ad hoc networks is crucial for operations. Messages exchanged in vehicle ad hoc network communications hold critical information such as road safety information, or road accident information and it is essential these packets reach their intended destination without any modification. A significant concern for vehicle ad hoc network communications is that malicious vehicles can intercept or modify messages before reaching their intended destination. This can hamper vehicle ad hoc network operations and create safety concerns. The multi-tier trust management system proposed in this paper addresses the concern of malicious vehicles in the vehicle ad hoc network using three security tiers. The first tier of the proposed system assigns vehicles in the vehicle ad hoc network a trust value based on behaviour such as processing delay, packet loss and prior vehicle behavioural history. This will be done by selecting vehicles as watchdogs to observe the behaviour of neighbouring vehicles and evaluate the trust value. The second tier is to protect the watchdogs, which is done by watchdogs’ behaviour history. The third security tier is to protect the integrity of data used for trust value calculation. Results show that the proposed system is successful in identifying malicious vehicles in the VANET. It also improves the packet delivery ratio and end-to-end delay of the vehicle ad hoc network in the presence of malicious vehicles.

I am grateful to the individuals that participated in the clinical studies described in this thesis. I would like to thank them for their patience, generosity, and courage. Thanks to Dr. Udo Weishmann his mentorship and input while I carried out this project; our initial fortuitous meeting was to make-way for this influential collaboration. Thanks, Udo, for sharing the passion to help epilepsy patients which has motivated us throughout. Thanks to Becky Higginbottom and Amy Ibbotson, and all the Clinical Physiologists' at the Walton Centre for assisting me with patient profile collection and teaching me valuable epilepsy terminology and the methods at the Neurophysiology Department.Thanks to the NRES committee London-Dulwich (HEALTH RESEARCH AUTHORITY) for supporting me in the design of clinical studies, and for helping me with the NHS IRAS (Integrated Research Approval System). Thanks to Dave Watling for making the ethical aspects of the studies at The Walton Centre possible. The App system used in these studies could not have been built without the help of my colleague and fellow PhD researcher Oladotun Omosebi: his determination, positivity and skill will long live in the memory. I am hugely thankful for the input from my supervisory team; Professor

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The premises made in this paper put the future of personalisation in epilepsy into focus, a focus that shifts from a one-size fits all to a focus on the core of the epilepsy patients' individual characteristics. The emerging approach of personalised healthcare is known to be facilitated by the Internet of Things (IoT) and sensor-based IoT devices are in popular demand for healthcare providers due to the constant need for patient monitoring. In epilepsy, the most common and complex patients to deal with correspond to those with multiple strands of epilepsy. These extremely varied kind of patients should be monitored precisely according to their identified key symptoms and specific characteristics then treatment tailored accordingly. Consequently, paradigms are needed to personalise this information. By focusing upon personalised parameters that make epilepsy patients distinct this paper proposes an IoT based Epilepsy monitoring model endorsing a more accurate and refined way of remotely monitoring the 'individual' patient.