Their digital society is dependent on complex dynamic telecommunications systems that support our activities and interactions, with increasingly more devices being connected and communicating each day. Managing these systems is a challenging task with time critical needs to provide real-time functionality to services – including healthcare, transport, finance, socialising, and other forms of interaction. Analysts need to ensure that networks are functional, from physical layers through to networking and application layers. At the same time, analysts need to identify and mitigate against threats which can materialise as denial-of-service attacks, targeted sabotage of users, or leaks of confidentiality.
In recent years, Machine Learning techniques have been applied to manage service level provisions, and yet security threats continue to challenge this domain. A major challenge in this domain is to establish cyber situational awareness, in terms of the current landscape and the anticipated future events, and how to effectively integrate human-machine collaboration to best utilise machine learning approaches whilst enabling analysts to best home in on contextual aspects of security threats, all the while doing so in a real-time manner that causes little or no disruption to the end-user service.
This PhD research will explore the current trends of machine learning and communication networks, recognising the role of Machine Learning as an enabler of cyber security but also as introducing another potential attack vector. In this manner, analysts need to determine how best to collaborate with the system, to identify what should be automated, what should be human-assisted, and what should be human-led investigation. Fundamentally, the research question that this project will seek to resolve is how best to inform real-time decision making in complex communication networks when potential attack vectors are observed such that service and security are both appropriately maintained.
The successful candidate will work closely with their industry partner, Ribbon Communications Ltd. The research will address real-world challenges as recognised in practice by their partners. In turn, the successful candidate will link between academia and industry to deliver real-world impact.
More than year
36 - 60
More than year
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