Academic Centre of Excellence in Cyber Security Research - Queen's University Belfast

Lead Research Organisation: Queen's University of Belfast
Department Name: Electronics Electrical Eng and Comp Sci

Abstract

Our world has become increasingly digitised, affecting how we communicate, manage our finances, access healthcare and even interact with household devices. With more of our information held digitally and connected across multiple devices as well as in the cloud, significant new cyber security challenges are emerging. How can we process and transmit large volumes of information created by citizens, enterprise and government securely? How do we meet the demand for innovative technologies and solutions to counter the threat? How do we produce the next generation of industry leaders, new ventures and a skilled workforce to sate the ever growing appetite for cyber security experts globally? These are some of the global challenges being tackled by CSIT every day.

CSIT was awarded the a Queen's Anniversary Prize for Higher and Further Education in 2015 for its work in strengthening global cyber security and protecting the online activity of billions of internet users around the world. It is already internationally recognised as performing state-of-the-art research in a number of key areas. These include:

Device authentication - Development of Post-quantum cryptographic solutions, low power cryptosystems for RFID and IoT devices, high speed integer based fully homomorphic encryption

Secure ubiquitous networking - Securing real-time connectivity between devices, sensors and cloud resources. Mobile malware detection methods to counteract advanced evasion technologies such as polymorphic and metamorphic obfuscation. Securing highly distributed networks for critical infrastructures. Securing software defined and highly virtualised networks.

Security analytics and event management - Forensic data clustering and anomaly detection. Online graph-based mining algorithms to process data in real-time. Data mining approaches to learn inference rules about events and engage multi-criteria decision making for autonomous cyber security threat assessment

A key aspect of the Centre is the commercialisation of the research through a dedicated team of commercial and business development staff. This includes mechanisms such as the CSIT Membership programme, spin outs, a cyber security incubator programme (CSIT Labs), licensing, knowledge transfer partnerships and contract research and development.

Planned Impact

A critical part of CSIT's remit is to ensure commercialisation and knowledge transfer and the impact of this in the commercial environment and wider society. It is important to note that CSIT considers "commercialisation" to be synonymous with economic development and not in the more narrow sense of exploitation of technology. This wider economic agenda is supported by the total package of funding from EPSRC/Innovate, Invest NI as well as the ACE-CSR scheme.

These activities include the following:

- CSIT membership (full and associate) and related commercialisation discussions
- Contract research and development
- Licensing opportunities
- CSIT Labs and the resulting company creation/support/growth
- Internal innovation programmes/further development of the internal innovation culture
- Spin out - creation and development
- Spin in - support and facilitation
- NI Cyber cluster development, locally and as part of a wider UK and international ecosystem. Ultimately job creation and the 5000 jobs by 2026.
- Foreign Direct Investment support
- Skills development - MSc, PhD and training course delivery
- Participation in standards bodies
- Marketing and PR strategy, Annual Summit promotion and delivery, stakeholder engagement

Publications

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Luo C (2019) A benchmark image dataset for industrial tools in Pattern Recognition Letters

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Zhang L (2018) BoMW: Bag of Manifold Words for One-Shot Learning Gesture Recognition From Kinect in IEEE Transactions on Circuits and Systems for Video Technology

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Zhang S (2018) Point-to-Set Distance Metric Learning on Deep Representations for Visual Tracking in IEEE Transactions on Intelligent Transportation Systems

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Zhang X (2018) Spatial Sequential Recurrent Neural Network for Hyperspectral Image Classification in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

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Zhang X (2018) Hybrid Unmixing Based on Adaptive Region Segmentation for Hyperspectral Imagery in IEEE Transactions on Geoscience and Remote Sensing