Reference Number: EMRC-RK-2018-1-PhD
This project will investigate into developing a resilient security framework that is adaptable and intelligent with learning abilities for unknown attacks. The proposed framework can be utilized into various use cases especially, vehicular cyber physical systems (VCPS), vehicular communication, smart cities, smart healthcare, etc.
Specific Requirements of the Project
Skills required: Good mathematical background, programming experience and familiar with using language such as Matlab and Python.
Applicants should hold or expect to hold a 2.1 Hons (or equivalent) undergraduate degree or MSc in a relevant discipline such as Computer Science, Electrical and Electronic Engineering, Communication Engineering, Applied Mathematics, etc.
Project Aims and Objectives
Internet of Things (IoT) and cyber physical systems consists of constrained devices, i.e. with low power, processing speed and memory. This means the security measures that evolved during the last few decades cannot be directly implemented therefore, new lightweight cryptographic standards are required that can run on constrained devices such as car engines, light bulbs, refrigerators, smart meters, etc. Also, the security models and mechanisms used currently are hard to change or reuse and are not reconfigurable to adapt to the threats. Energy optimization and security measures are reciprocal since implementing rigorous algorithms that require higher computing resources will demand more energy, therefore a balance is required, for e.g. is it possible to implement a key size that is small enough requiring less computing resources but still secure enough for the necessity.
The purpose of this project is to develop a security architecture that implements lightweight energy efficient cryptographic algorithms and self-configurable system strategy that can detect, thwart and prevent potential threats and allow the system to self-adapt for any future threats (because of dynamic changing conditions of the IoTs) by applying intelligent learning algorithms. The security framework thus developed can be used in the context of various use cases such as smart homes, smart healthcare or vehicular communication.
Specific aims and objectives of the project are to be identified in discussion with the academic supervisors during the first 3 months of the project.
Project is open to: Home/EU and overseas
Informal enquiries can be made to Dr Rupak Kharel
Tel 0161 247 1655 email [email protected]