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MEng e-voting project published in a journal paper

As part of a 2021/2022 MEng group project, Horia Druliac, Matthew Bardsley, Chris Riches, and Christian Dunn implemented a fully functional end-to-end (E2E) verifiable online voting system and conducted a successful trial among the residents of New Town in Kolkata, India during the 2022 Durga Puja festival celebration. This was the first time an E2E online voting system was built and tested in India. The feedback was overwhelmingly positive. Full details about the implementation, the trial and the voter feedback are written in a paper, published in the Journal of Information Security and Application. A free version of the paper is available on IACR e-print as a technical report. Also, see the earlier news item about this Durga Puja trial.

Professor Feng Hao, who supervised this group project, commented: “This is great teamwork. The four MEng students worked relentlessly for nearly a year, with good assistance from Luke Harrison and Professor Bimal Roy. The e-voting system was developed at an industry standard and worked flawlessly during the Durga Puja trial. Several government officials from India also helped us, providing invaluable support for the trial. We sincerely thank them in the acknowledgement section of the paper.”

Mustafa Yasir Presents Project Work at the 3rd Annual Workshop on Graph Learning Benchmarks at KDD 2023

Mustafa Yasir, a former Warwick Department of Computer Science student who graduated in Summer 2023, wrote up and presented an academic paper on the work carried out as part of his third year project. The paper was accepted to the 3rd Annual Workshop on Graph Learning Benchmarks at KDD 2023, and was presented in California by Mustafa.

Mustafa's third year project idea, supervised by Dr Long Tran-Thanh and titled 'Extending the Graph Generation Models of GraphWorld', started whilst he was interning at Google last summer. Mustafa contacted some researchers at the company working in the Graph ML space, to ask for any relevant project ideas. He bumped into a team who had just published GraphWorld: a tool to change the way Graph Neural Networks are benchmarked, by creating synthetic graph datasets through graph generation models – as opposed to using real-world datasets that are limited in their generalisability and present a major issue facing the field of Graph Learning.

However, since GraphWorld only used a single graph generation model in this process, Mustafa integrated two additional models with the system, ran large-scale GNN benchmarking experiments with these models and published his code to Google’s official GraphWorld repository. The project provides a significant advancement to researchers across the field looking to benchmark models and guide the development of new architectures.

Dr Long Tran-Thanh commented:

What Mustafa and the GraphWorld team has been working on is very important for the machine learning and AI research communities. In particular, there has been a vocal criticism against the whole field that most models are trained on the same public datasets (e.g., ImageNet, MNIST, etc), therefore are not diverse enough. One way to mitigate this issue is to generate realistically looking synthetic data. This need is especially of importance in within the graph learning community. GraphWorld’s aim is to address this exact problem by creating a powerful and convenient tool that can generate a diverse set of graphs, ranging from large social network-style graphs to molecule-inspired ones. Joining this project with the Google researchers is a huge opportunity for Warwick students to participate in a very impactful project.

Spying on the Spy: Security Analysis of Hidden Cameras

When you purchase an IP-based spy (hidden) camera for surveillance, are you aware that others may be spying on what you are watching? Recent research by Samuel Herodotou in the Department of Computer Science, Warwick, as part of his third-year undergraduate dissertation project under the supervision of Professor Feng Hao, has revealed a wide range of vulnerabilities of a generic camera module that has been used in many best-selling hidden cameras. Exploiting these vulnerabilities, an attacker may capture your hidden camera's video/audio streams from anywhere in the world, and furthermore, take complete control of the camera as a bot to attack other devices in your home network. To launch the attack, all the attacker needs to know is merely your hidden camera’s serial number. It is estimated that these vulnerabilities affect millions of hidden cameras, mostly sold in America, Europe and Asia. The (insecure) peer-to-peer network that is used by the affected cameras is also being used by 50 million IoT devices as a general communication platform. Hence, many millions of other IoT devices may also be affected. Researchers have responsibly disclosed findings to the manufacturers, and a CVE has already been assigned. Samuel will present this research work at the 17th International Conference on Network and System Security (Canterbury, UK, 14-16 August 2023). More details can be found in the paper.

Computing Your Career 2022

We recently hosted our flagship careers event, find out what went on and who attended.

Mon 07 Nov 2022, 12:00 | Tags: Undergraduate

Warwick Celebrates

We welcomed back previous UG students on the 12th July for the Warwick Celebrates event. Thank you Ranko for your inspiring speech from the balcony!

Fri 22 Jul 2022, 10:41 | Tags: Undergraduate

Innovation 2022

The inaugural DCS Innovation competition was held on 17th June and was a great success.

Fri 15 Jul 2022, 12:50 | Tags: Undergraduate

Computer Science student Jasmine Brown recognized on MLH Top 50 List

Jasmine Brown, a Computer Science student at the University of Warwick has been named one of 2022’s MLH Top 50–a list of the organization’s most inspiring community members. The recipients are recognized for their exceptional contributions to the tech ecosystem & STEM education.

Tue 12 Jul 2022, 09:50 | Tags: Undergraduate

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