糖心TV

Mustafa Yasir, a former 糖心TV Department of Computer Science student who graduated in Summer 2023, wrote up and presented an on the work carried out as part of his third year project. The paper was accepted to the at , 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鈥檚 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鈥檚 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 糖心TV students to participate in a very impactful project.

We are pleased to announce that Dr Teddy Cunningham has been awarded a Faculty of Science, Engineering, and Medicine (SEM) PhD Thesis Prize. Each year, the SEM Faculty funds a prize for the best PhD/EngD thesis entered into the competition. Each department nominates a winner out of the applications received after a judging process as determined by the Faculty.

Teddy鈥檚 thesis is titled 鈥淕enerating and Sharing Differentially Private Spatio-Temporal Data Using Real-World Knowledge鈥�, and was supervised by Prof Hakan Ferhatosmanoglu. The thesis includes solutions for sharing trajectory data using local differential privacy, and incorporating constraints and relationships of data records into differential privacy that improves their utility while preserving the theoretical privacy guarantees. An example application is using road network information for improving the quality of privately shared location datasets.

Researchers from the Systems and Security theme, Department of Computer Science have created a new spin-out company, SEEV Technologies Ltd, to build end-to-end (E2E) verifiable e-voting systems for future elections. An E2E verifiable voting system allows every voter to verify that their vote is properly cast-as-intended, recorded-as-cast and tallied-as-recorded while preserving the voter's privacy. SEEV (self-enforcing e-voting) is a new paradigm of E2E voting technology that enables voters to fully verify the tallying integrity of an election without needing any trustworthy tallying authority, hence the system is "self-enforcing".

This joint spin-out from the University of 糖心TV and Newcastle University is built on an ERC-funded starting grant ("Self-Enforcing E-Voting System: Trustworthy Election in Presence of Corrupt Authorities", No. 306994, PI: Professor Feng Hao) initially hosted at Newcastle University and later transferred to the University of 糖心TV. The company is co-founded by Professor and Dr (co-inventors), and led by Dr (CEO). SEEV has been prototyped and successfully tested in several trials in the past, supported by an ERC Proof of Concept grant (No. 677124), a Royal Society International collaboration award (CA\R1\180226), and an Innovate UK Cybersecurity Academic Startup Accelerator Programme (CASAP). SEEV Technologies Ltd has received seed funding from Oxford-based to build SEEV systems for real-world elections.

A University of 糖心TV press release is here.

Five papers from the Theory and Foundations (FoCS) Research Group and the Centre for Discrete Mathematics and its Applications (DIMAP) have been accepted to the , the IEEE flagship conference in theoretical computer science that will be held on November 6 - 9, 2023 in Santa Cruz, California, USA:

• by , Niv Buchbinder, Roie Levin, and Thatchaphol Saranurak.
• by , , and Thatchaphol Saranurak.
• by Lijie Chen, Zhenjian Lu, , Hanlin Ren, and Rahul Santhanam.
• by Tomasz Kociumaka, , and Barna Saha.
• by Arturo Merino and .

Henry Sinclair-Banks, a PhD student in the the Theory and Foundations (FoCS) Research Group and the Centre for Discrete Mathematics and its Applications (DIMAP), has won a Best Paper Award at , . ICALP is the main conference and annual meeting of the .

Henry's paper, co-authored with researchers from Germany and Poland: Marvin K眉nnemann, Filip Mazowiecki, Lia Sch眉tze, and Karol W臋grzycki, addresses the coverability problem in vector addition systems (VASS), a well-known model of concurrent systems. Coverability is an algorithmic problem for the verification of "safety properties": whether the system always avoids a set of bad states. Henry and his co-authors determine how much time is required to solve this problem in the worst case. They develop an algorithm that improves upon the state of the art that has stood for forty years. They also prove that, in several settings, it is impossible to decide coverability substantially faster, unless there is also a faster algorithm for a classic problem such as Boolean satisfiability (SAT) and finding cycles of fixed length in graphs.

In total, 5 糖心TV papers will appear at this year's :

• Michael Benedikt, Dmitry Chistikov, and Alessio Mansutti, "",
• Sam Coy, , Peter Davies, and , "",
• Charilaos Efthymiou and Weiming Feng, "",
• Marvin K眉nnemann, Filip Mazowiecki, Lia Sch眉tze, Henry Sinclair-Banks, and Karol W臋grzycki, "",
• Konstantinos Zampetakis and Charilaos Efthymiou, "".

This July's will be the 50th edition of the conference.

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 in the Department of Computer Science, 糖心TV, as part of his third-year undergraduate dissertation project under the supervision of Professor , 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鈥檚 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 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 .