All Projects

Continue development of (parts of) an Internet scanning infrastructure tailored to Ireland

Stephen Farrell (email | all projects)

Scanning public-facing Internet services in order to detect security- and privacy-relevant patterns and problems is becomming well-trodden ground. Typical studies attempt Internet-scale IPv4 scans, e.g., to detect uses of outdated ciphers in uses of the Transport Layer Security (TLS) protocol. More local scans (e.g., https://eprint.iacr.org/2018/299) could however produce results that are easier to translate into … Read more

Compare censorship experienced in Ireland with another country

Stephen Farrell (email | all projects)

The project is to survey censorship measurement tools and data sets (e.g. https://ooni.org/ and similar), to compare and contrast those, and then use some subset of the identified tooling and data to compare the censorship situation for Internet users based in Ireland against the position of users based in some other country, to be agreed … Read more

Verification for Ethereum Smart Contract Vulnerabilities

Vasileios Koutavas (email | all projects)

[Multiple projects] Smart Contracts (SCs) are a cornerstone technology for decentralised finance and decentralised applications which are in the core of Ethereum. Of particular urgency is the problem of security for SCs as high financial incentives make them a prime target for attacks, and blockchain immutability make them impossible to fix once deployed. Numerous exploits … Read more

[Taken] Individual Fairness through Time

Andrea Patane (email | all projects)

Individual fairness concerns the ability of a machine learning model to not being affected in its predictions by one or more sensitive features, such as gender, race, age etc.Recent methods developed techniques for the formal analysis and approximation of fairness in the case of deep Neural Networks (NNs). However such techniques are restricted to simple … Read more

[Taken] Deep learning for physiological signal

Andrea Patane (email | all projects)

Deep learning has recently achieved state-of-the-art performances in many computer vision classification tasks. In this project we’ll look into developing a tailored deep learning solution based on Neural Network for a problem related to classification with physiological signals. The project will go into details of architecture selection, hyper-parameter learning, validations, and best training practice of … Read more

[Taken] Fair training through uncertainty

Andrea Patane (email | all projects)

Deep learning, in particular Neural Networks (NNs), has achieved state-of-the-art results in many applications in the last decade. However, the way these models work and operate is still not fully understood, and in many ways they are approached as black-box when deployed in practice.Unfortunately, this raises several concerns about their suitability to deal with sensitive … Read more

Deep Learning for Radio Signal Processing

Viet Quoc Pham (email | all projects)

With the great capability of learning high-level representational features of unstructured data automatically, deep learning is acknowledged as a powerful machine learning algorithm for radio signal processing. For example, convolutional neural networks (CNNs) are leveraged to develop automatic modulation classification frameworks in [1]-[3]. CNN and its combination with Vision Transformers are also used to design … Read more

Student led project in education

Emma Howard (email | all projects)

I am happy to supervise a student led project in the area of: online learning or the use of technology (e.g., Gen AI or lecture capture) in Higher Education; data analysis or applied statistics in the areas of higher education or student support services; and, statistics/mathematics education in Higher Education. Students interested in such a … Read more

Wireless Artificial Intelligence | Federated Learning

Viet Quoc Pham (email | all projects)

Federated learning is a paradigm breakthrough shift in AI for data privacy preservation. Unlike conventional artificial intelligence (AI) techniques, federated learning does not require the users to share the data, but only the AI model parameters. As such, federated learning has found notable successes in numerous applications (e.g., Google keyboard, localization, security, and data sharing) … Read more