Start typing here..From assisting radar systems to better detect targets with accuracy and speed, identifying anomalies in large-scale surveillance networks to transforming imagery into geospatial information to improve situational awareness, machine learning (ML) is revolutionising the way Defence personnel gather and analyse intelligence.
As part of a four-year research project, funded under the Defence Trailblazer Industry Research Program, DEWC Services will support a PhD student to explore how combining advanced technology with network analysis and linguistic understanding can enable Defence to understand how best to employ networks for military applications.
Working closely with leading researchers at the University of Adelaide’s School of Computer and Mathematical Sciences, the PhD student will develop an initial prototype that employs ML models and techniques to analyse a network using real-world data.
DEWC Services is a leading Defence industry partner providing technical expertise across Command, Control, Communications, Computers, Intelligence, Surveillance, Reconnaissance and Electronic Warfare (C4ISREW). In supporting the research challenge, the PhD student will leverage the company’s unique industry insights and partnerships in the Defence sector.
“We are delighted to support the professional development of one of our very own cyber experts, while also driving research that will ultimately lead to new technologies that enhance Australia’s defence capabilities and posture,” DEWC Services Director – Science and Technology, Dr Tim McKay said.
Machine learning (ML) has become a critical technology in the Defence sector and is transforming the way Defence operates across intelligence, surveillance, reconnaissance and electronic warfare. Now a key component in modern warfare systems, ML is vital in processing large volumes of complex data, recognising patterns and providing information that supports operational decisions.
“This project explores ways we can combine ML models to analyse network traffic using a range of techniques, such as OS fingerprinting, communication protocol classification, natural language processing models to help infer the intent of the network,” Dr McKay said
“For example, ML learning models could analyse a network by gathering data and making inferences about what operating systems are used and communications between them, which would give an operator greater insight into the network.
“Using ML to automate and congregate information from various sources to infer and predict a network is an effective reconnaissance tool and can help operators evaluate possible threats in an unobtrusive manner.”
There is an urgent need to build workforce capability in Defence-related contexts, so we’re delighted to work closely with our partners to develop industry-led PhD and Masters offerings. The scholarships have been specially designed to address the current and future needs of defence, with real-world projects on offer.
The industry mentorship, onsite internships and academic guidance are just some of the ways the program enables a supportive research journey that fosters deep technical knowledge and a deeper understating of Defence-based applications for STEM fields, among others”, says Heather Nicoll, General Manager of Workforce, Innovation & Culture at Defence Trailblazer.
About the Trailblazer
Defence Trailblazer is a collaborative partnership between the University of Adelaide and UNSW and over 40 industry partners, with support from the Australian Government Department of Education. The Defence Trailblazer aims to strengthen Australia’s defence sovereign capabilities by developing cutting-edge technologies and solutions, while simultaneously equipping the next generation of innovators with specialised knowledge and skills to meet the current and future needs of Defence.
This Defence Trailblazer is a four-year program funded by a $50 million grant from the Department of Education and matched by $25 million (cash and in-kind) from each of the universities, with an additional contribution of approximately $100 million from industry.