CyberSecurity Research   UCC

Security · Privacy · Cryptography


The group is currently involved in the following projects. Some of these run in collaboration with other research groups and centers at UCC. Names of investigators that are members of the Security group are underlined.

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Personal Voice Assistant Security and Privacy (PVAsec)

Led by: Prof Utz Roedig
Funded by: Science Fundation Ireland (Frontiers fort the Future Award)

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Personal Voice Assistants (PVAs) such as Amazon Echo, Siri or Google Home are now commonplace and are increasingly used for interaction with phones, tablets, PCs and smart environments such as automated homes or cars. PVAs collect sensitive information such as conversations and sound cues and are used to access important computer systems requiring access control.

The project PVASec: Personal Voice Assistant Security and Privacy aims to advance our understanding of security and privacy issues in the PVA context. The project will make contributions in four closely related work areas: (i) PVA Privacy: methods for recording consent management, methods for recording tracking, new insights into information disclosure; (ii) PVA Security: methods for speaker authentication, methods to detect voice command injection; (iii) PVA Denial of Service (DoS): analysis of acoustic DoS and design of detection methods and countermeasures; (iv) PVA Acoustic Sensing: acoustic sensing approaches, detection and countermeasures for acoustic sensing.

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Holistic Human Sensing for Health, Aging and Wellness (HOLISTICS)

Led for Insight (UCC) by: Prof Ken Brown – Co-Investigators: Dr Paolo Palmieri, Prof Barry O'Sullivan
Funded by: Department of Enterprise (Disruptive Technologies Innovation Fund)

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HOLISTICS will create for the first time in Ireland, a disruptive Smart Wearables Industry Value Chain to deliver end-to-end HealthTech solutions based on emerging human-centric intelligent sensors and their wireless communication (abbrev. WSN) to support new products.

The project consortium is composed by: Tyndall National Institute, DABL, PMD Solutions, De Royal, Setanta, Lero (UCC), Sanmina, Design Partners, VRAI, Henkel, ADI, HRB CRF-C, Insight (UCC).
Dr Paolo Palmieri leads the research effort on protocol security and cryptography, aimed at guaranteeing the security of the devices an sensors communication.

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Big data pRocessing and Artificial Intelligence at the Network Edge (BRAINE)

Led in UCC by: Prof Cormac Sreenan – Co-Investigators: Prof Utz Roedig, Prof Barry O'Sullivan
Funded by: European Union Horizon 2020 Programme - ECSEL Joint Undertaking

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By lowering the barriers for utilising edge computing for artificial intelligence applications, BRAINE will open the door for European SMEs to leverage state of the art technologies, driving their development and growth as industry leaders in their sectors. The BRAINE project’s overall aim is to boost the development of the Edge framework and, specifically, energy efficient hardware and AI empowered software systems, capable of processing Big Data at the Edge, supporting security, data privacy and sovereignty.

The project has a total budget of €16.3M, and and is part of the ECSEL Joint Undertaking (JU) programme. The JU receives support from the EU's Horizon 2020 and from the national authorities of Italy, Poland, Nederland, Israel, Ireland, Hungary, Germany, Switzerland, Finland, and Czech Republic. In the project, Prof Utz Roedig contributes to research on a future-proof Edge security framework and associated infrastructure.

Cryptographic privacy-preserving protocols for location based services

Led by: Dr Paolo Palmieri
Funded by: School of Computer Science & IT, UCC

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Location and mobility data are highly sensitive, as they can be used to infer a number of other personal and sensitive data on an individual, including social relationships, habits, and in some cases religion or health conditions. The protection of location information is therefore crucial to preserve the privacy of users of location-aware devices and services, such as smartphones and wearables, connected vehicles and smart transportation systems, e-tolling, and cameras with face recognition among others.

This project investigates cryptographic protocols based on partially homomorphic encryption and efficient probabilistic data structures for location information. Research will focus on mutual privacy, in the secure multi-party context, were both the user and service provider have an interet in protecting their inputs.