Honours and Masters project

The security threat by quantum computing to almost all currently used digital signatures was triggered by the discovery of Shor’s quantum algorithm, which efficiently breaks the two problems underlying the security of these schemes, namely integer factoring, and elliptic curve discrete logarithms (ECDLP). When quantum computers become widespread, all security for the current digital signatures that are widely used to secure a wide range of systems is lost.

Digital provenance refers to the process of verifying and tracing the origins, lifecycle, and integrity of digital content. C2PA (Coalition for Content Provenance and Authenticity) is an initiative founded by multiple technology and media companies, aiming to address the increasing concern of misleading information and disinformation on the internet in the age of AI. The main objective of C2PA is to establish a standardized approach for digital content provenance, which essentially means tracing the origin and verifying the integrity of digital content.

Australia’s cybersecurity infrastructure, particularly in IoT networks, must be strengthened to meet evolving standards set by international bodies like NIST and the NSA. This project will support Australian organisations in adapting to quantum-safe standards, ensuring the protection of sensitive data and critical system

Digital signatures are asymmetric cryptographic schemes used to validate the authenticity and integrity of digital messages or documents. The signer uses their private key to generate a signature on a message. Then, this signature can be validated by any verifier who knows the signer’s corresponding public key. Sometimes a digital message might require signatures from a group of signers. The naïve method to achieve this goal is collecting distinct signatures from all signers.

Climate change will affect us all, and we have to do everything we can to minimize the magnitude of change. Investments in renewable generation help to reduce the impact of energy usage on the supply side, but that will not get us all the way there, especially in the near term. Consumers will also have to become much more efficient with their energy use.

Discussion of dangers of artificial intelligence (or artificial superintelligence, ASI) being an ambitious subordinate and ultimately taking over control from humans goes back at least as far as R J Solomonoff (1967).  R J Solomonoff (1985) gives an approximate time-frame in which this might occur.

    DNA or RNA motif discovery is a popular biological method to identify over-represented DNA or RNA sequences in next generation sequencing experiments. These motifs represent the binding site of transcription factors or RNA-binding proteins. DNA or RNA binding sites are often variable. However, all motif discovery tools report redundant motifs that poorly represent the biological variability of the same motif, hence renders the identification of the binding protein difficult.

Using relevant available data-sets, we compare appliance usage across households of different demographics.  We then use machine learning techniques to infer how different households use different appliances at different times, resulting in diverse energy consumption behaviours. 

Rare neurodegenerative diseases, including the hereditary cerebellar ataxias, pose significant challenges for disease monitoring. Small patient cohorts, heterogeneous progression patterns, and slow rates of progression make it difficult to track disease change using conventional biomarkers. Although clinical rating scales remain the standard for assessing severity, they are subjective, prone to measurement noise, and often lack sensitivity to subtle longitudinal decline.

Introduction