Summary of the project: Randomness extraction is the heart of cryptography and cyber security. The whole concept of having a secure communication comes from the assumption that the computing devices are able to generate high entropy randomness. This means an adversary cannot predict the next random bit while it has access to the infinite history of previous bits. Generating random numbers is an ongoing research not only in cyber security but also other fields such as machine learning and Monte Carlo simulation studies. Generating randomness using algorithmic approach is called Pseudo Random Number Generation (PRNG) and extracting randomness from a third-party device and a random phenomenon is called True Random Number Generation (TRNG). While it is very convenient to generate random bits inside a computer using an algorithm, PRNG is very resource hungry and is not suitable for applications such as medical implants (we refer to them as extreme IoT devices). Extracting randomness from a third party could be a solution to secure the communication of these extreme IoT devices among themselves or to other devices. Several methods have been proposed in literature for using body physiological signals for randomness extraction. This project is looking into randomness extraction methods, randomness tests and development of secure communication using extracted randomness.
For any additional information about the project please contact Prof. Hassan Chizari firstname.lastname@example.org .
Brief: This is a 3-year Full-Time PhD Studentship only for home (UK) applicants. This PhD studentship covers the Fees + 10K stipend annually, where 1 day per week is spent engaging in demonstrator type activity for the School of Computing and Engineering.
The start of the PhD is March 2022.
Main supervisor: Associate Professor Hassan Chizari
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