Honours and Masters project

Deepfakes detection deals with machine learning methods, which detect if an image/video/audio sample is manipulated with a generative AI software. In recent years, deepfakes have been increasingly used for malicious purposes, including financial fraud, misinformation campaigns, identity theft, and cyber harassment. The ability to generate highly realistic synthetic content poses a serious threat to digital security, privacy, and trust in media. This project will develop methods for detecting deepfakes.

People are continuously receiving unsolicited emails where phishers impersonate legitimate organisations or trusted sender to harvest victim credentials. The rapid advance of AI boosts recent automatic detection of phishing attempts but also provides hackers with the opportunities to build increasingly sophisticated phishing tactics to bypass the filter. While attackers leverage social engineering to exploit human weakness, human skills can be a powerful component in cyber defence such as cognitive function and professional judgment.

Demand forecasting is the basis for a lot of managerial decisions in companies. During the last four decades, researchers and practitioners have developed numerous quantitative and qualitative demand forecasting models including statistical, machine learning, judgmental, and simulation methods.

Using digital technologies (such as 3D printing, soundscapes, beacon navigation), this project will explore the creation accessible cultural experiences for people who are blind or have low vision (BLV). Accessible materials and space design will be developed and evaluated to provide an evidenced-based framework for producing inclusive experiences with arts and culture, such as Art Galleries. Current partners include the Bendigo Art Gallery and Science Gallery Melbourne.

As part of this project, you will work closely with a community organisation or NGO (this can either be an organisation that you have existing links with or we will connect you with one of our partner NGOs). Working in collaboration with the org, you will find out challenges they face in giving voice to their communities/beneficiaries that can be addressed through social media (for instance, perhaps they want to run an awareness raising campaign about the difficulties faced by the community and they want the communities to be very involved in this).

This project aims to develop effective machine learning algorithms for detecting deepfake videos, which have become a significant concern for disinformation and cybersecurity. The objectives include pre-processing the data for feature extraction, and training machine learning models to accurately classify videos as either real or manipulated. The methodology involves using advanced techniques such as convolutional neural networks, recurrent neural networks or video vision transformer models to analyse visual and temporal patterns in the videos.

This project aims to develop privacy-preserving deepfake detection techniques that enable accurate and secure identification of synthetic audio and video content without exposing sensitive user data. Traditional detection methods often require access to raw audio or visual inputs, raising significant privacy concerns, especially in scenarios involving personal or biometric data.

Mis/disinformation (also known as fake news), in the era of digital communication, poses a significant challenge to society, affecting public opinion, decision-making processes, and even democratic systems. We still know little about the features of this communication, the manipulation techniques employed, and the types of people who are more susceptible to believing this information.

This project extends upon Prof Whitty's work in this field to address one of the issues above.

Background:

Imagine the human brain as a complex electrical grid, with over 80 billion neurons (nerve cells) acting as power stations. These power stations need to send electrical signals to each other efficiently. Myelin, a special lipid sheath, wraps around the neuron processes (axons) like insulation around electrical wires. This insulation ensures that the signals travel quickly and without losing strength, giving the brain’s “white matter” its name (Figure 1A).

The DNA inside a cell is not randomly distributed but rather organized in a structure called chromatin. This non-random distribution has important implications for the functioning of cellular programs. The basic building block of this organisation system is the nucleosome. The nucleosome consists of a short piece of DNA wrapped around a protein core, with millions of nucleosomes are present in the cell’s nucleus. The orientation of nucleosomes with respect to each other and the way they pack the genomic DNA determine the architecture of chromatin.…