Honours and Masters project

Verifiable Dynamic Searchable Symmetric Encryption (VDSSE) enables users to securely outsource databases (document sets) to cloud servers and perform searches and updates. The verifiability property prevents users from accepting incorrect search results returned by a malicious server. However, the community currently only focuses on preventing malicious behavior from the server but ignores incorrect updates from the client, which are very likely to happen in multi-user settings. Indeed most existing VDSSE schemes are not sufficient to tolerate incorrect updates from users. For instance,…

The increasing integration of Large Language Models (LLMs) into various sectors has recently brought to light the pressing need to align these models with human preferences and implement safeguards against the generation of inappropriate content. This challenge stems from both ethical considerations and practical demands for responsible AI usage. Ethically, there is a growing recognition that the outputs of LLMs must align with laws, societal values, and norms.

The last several years have witnessed the promising growth of AI-empowered techniques in mobile devices, from the camera to smart assistants. Users can find traces of AI in almost every aspect of mobile devices.

With the glow of digital information techniques, mobile systems are powerful ever and occupying more market shares. Just like wildly used social media sites, e.g. Facebook and Twitter, smartphone usage is up to 80% by 2020. In parallel to this trend, many companies are trying to incorporate Artificial Intelligent especially deep learning empowered applications into devices to further ease the life of people.

Graph neural networks (GNNs) are widely used in many applications. Their training graph data and the model itself are considered sensitive and face growing privacy threats.  

Electricity is an essential part of modern life and the economy. Driven by a combination of policy support and rapidly falling costs of low-carbon technologies, Australia is experiencing a sharp rise in the deployment of distributed energy sources (DERs). Typical DERs include wind, solar photovoltaics (PV), battery storage, and electric vehicles (EVs) on the consumer side.

Propositional satisfiability (SAT) is a well-known example of NP-complete problems. Although NP-completeness may be perceived as a drawback, it allows one to solve all the other problems in NP by reducing them to SAT and relying on the power of modern SAT solvers. This is confirmed by a wealth of successful examples of use cases for modern SAT solving, including generalisations and extensions of SAT as well as a wide variety of practical applications in artificial intelligence (AI).

Online fraud, also referred to as cyberscams, is increasingly becoming a cybersecurity problem that technical cybersecurity specialists are unable to effectively detect. Given the difficulty in the automatic detection of scams, the onus is often pushed back to humans to detect. Gamification and awareness campaigns are regularly researched and implemented in workplaces to prevent people from being tricked by scams, which may lead to identity theft or conning individuals out of money.

Using Adobe Photoshop to generate or edit images is old news, we don't need to edit using our hand and mouse, nor even a stylus pen.  All we need to do is command the gen AI to do it.

Right now the AI literature is trending with many techniques that enable to generate or edit realistic pictures by simply describing them: let there be pictures.

Gen AI has taken the world by storm, it's been applied to many disciplines including in pure sciences.  Notably, Google Deepmind used their graph deep learning based generative AI model (GNoME) to discover millions of new materials, as well as their AlphaFold to predict the structure & interactions of all of life’s molecules.