Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
Privacy Preservation over 5G and IoT Smart Devices. This project aims to investigate privacy preservation protocols in a 5G integrated IoT environment through an analysis of the depth of smart-device use in common smart domains. 5G’s addition to IoT-based smart devices will be effectively deployed and utilised by a large majority of individual and organisation-based users. The knowledge-based ontology and tools developed in the project will help form the new privacy preservation mechanisms that ....Privacy Preservation over 5G and IoT Smart Devices. This project aims to investigate privacy preservation protocols in a 5G integrated IoT environment through an analysis of the depth of smart-device use in common smart domains. 5G’s addition to IoT-based smart devices will be effectively deployed and utilised by a large majority of individual and organisation-based users. The knowledge-based ontology and tools developed in the project will help form the new privacy preservation mechanisms that are required for the 5G enabled environment. The construction of new AI-based tools and testing facilities as well as the generation of new knowledge in the field of privacy preservation and collaboration between universities are expected outcomes of this project. Read moreRead less
Learning the Focus of Attention to Detect Distributed Coordinated Attacks. Cyber security analysts need to detect and respond to attacks as soon as possible, to minimise the damage attackers can inflict. However, the growth in highly distributed attacks that span multiple networks has meant that massive volumes of data need to be analysed. While machine learning techniques can help filter the data, we need techniques that can automatically provide a focus of attention for analysts on the most re ....Learning the Focus of Attention to Detect Distributed Coordinated Attacks. Cyber security analysts need to detect and respond to attacks as soon as possible, to minimise the damage attackers can inflict. However, the growth in highly distributed attacks that span multiple networks has meant that massive volumes of data need to be analysed. While machine learning techniques can help filter the data, we need techniques that can automatically provide a focus of attention for analysts on the most relevant observations. Our aim is to devise a novel suite of attention mechanisms that can focus the search of machine learning techniques for cyber security. The results of this project will improve the accuracy and efficiency of detecting distributed attacks across multiple networks.Read moreRead less
Massive Data Reading with Mobile Data Collectors for the Internet of Things. The Internet of Things (IoT) supports the connectivity of almost everything including powerless simple devices (such as radio frequency identification (RFID) tags), making it an indispensable technology for future industry and business. This project is to develop systematic and cost-effective approaches by leveraging existing cellular networks for the connectivity of simple sensors/devices using mobile data collectors ( ....Massive Data Reading with Mobile Data Collectors for the Internet of Things. The Internet of Things (IoT) supports the connectivity of almost everything including powerless simple devices (such as radio frequency identification (RFID) tags), making it an indispensable technology for future industry and business. This project is to develop systematic and cost-effective approaches by leveraging existing cellular networks for the connectivity of simple sensors/devices using mobile data collectors (such as smart phones) so that their information becomes available to IoT applications via cellular systems. For example, products’ information stored in RFID tags or power-limited sensors' data can be provided to logistic or IoT applications, respectively, without building dedicated systems via existing cellular systems.Read moreRead less
Creating a Perceptive Mobile Network Using Joint Communication and Sensing. This project aims to develop foundational technologies for an innovative perceptive mobile (cellular) communication network that is also capable of ubiquitous radio sensing. It is expected to generate groundbreaking theorems and algorithms that will significantly advance the knowledge of joint communication and sensing. The intended outcomes are an innovative large-scale sensing solution capable of real-time 3D-plus radi ....Creating a Perceptive Mobile Network Using Joint Communication and Sensing. This project aims to develop foundational technologies for an innovative perceptive mobile (cellular) communication network that is also capable of ubiquitous radio sensing. It is expected to generate groundbreaking theorems and algorithms that will significantly advance the knowledge of joint communication and sensing. The intended outcomes are an innovative large-scale sensing solution capable of real-time 3D-plus radio imaging of the world, and enhanced communications with improved quality and reliability. The technology will revolutionize traditional communication-only mobile networks. It will enable and boost expansive radio sensing applications in e.g. transportation, energy, agriculture, and security.Read moreRead less
Physical Layer Security for Wireless Machine-Type Communications. This project aims to provide new understanding and design guidelines to secure wireless communications among low-cost resource-constrained devices. This is achieved by advancing the fundamental theory of an emerging security paradigm named physical layer security. Expected outcomes of this project include a communication-theoretic framework to characterise the secrecy performance of communications over wireless networks, followed ....Physical Layer Security for Wireless Machine-Type Communications. This project aims to provide new understanding and design guidelines to secure wireless communications among low-cost resource-constrained devices. This is achieved by advancing the fundamental theory of an emerging security paradigm named physical layer security. Expected outcomes of this project include a communication-theoretic framework to characterise the secrecy performance of communications over wireless networks, followed by novel signal processing and transmission designs. The research outcomes should provide innovative solutions to safeguard commercial and industry Internet of Things networks, benefiting Australia's digital transformation.Read moreRead less
Developing Adversary-Aware Classifiers for Android Malware Detection. Smartphones have become increasingly ubiquitous in people’s everyday life. However, it was reported that one in every five Android applications were actually malware, considering that Android has taken 88% market share of mobile phones. As an effective technique, machine learning has been widely adopted to detect Android malware. However, recent work suggests that deliberately-crafted malware makes machine learning ineffective ....Developing Adversary-Aware Classifiers for Android Malware Detection. Smartphones have become increasingly ubiquitous in people’s everyday life. However, it was reported that one in every five Android applications were actually malware, considering that Android has taken 88% market share of mobile phones. As an effective technique, machine learning has been widely adopted to detect Android malware. However, recent work suggests that deliberately-crafted malware makes machine learning ineffective. In this project, we propose to develop a series of new techniques, such as 1) Android contextual analysis, 2) wrapper-based hill climbing algorithm, and 3) ensemble learning, to solve this problem. The outcomes will help Australia gain cutting edge technologies in adversarial machine learning and mobile security.Read moreRead less
Information systems theory for location-based educational services in informal learning environments. Creating technology enhanced learning experiences will be critical to the way we educate and engage with future generations. This project will seek to develop a stronger theoretical basis for understanding how location-based technologies can enhance learning outcomes of school students visiting three of Australia's leading cultural institutions.
Decimetre-level indoor positioning on Wi-Fi. This project aims to exploit both spatial and frequency diversities based on the multiple-input, multiple-out and frequency hopping techniques to achieve the goal of decimetre-level position accuracy by significantly increasing Wi-Fi bandwidth. Wi-Fi positioning is utilised in locations where GPS is blocked, typically this is within a structure. The project will design a set of mechanisms to facilitate Wi-Fi positioning, discover key principles to gui ....Decimetre-level indoor positioning on Wi-Fi. This project aims to exploit both spatial and frequency diversities based on the multiple-input, multiple-out and frequency hopping techniques to achieve the goal of decimetre-level position accuracy by significantly increasing Wi-Fi bandwidth. Wi-Fi positioning is utilised in locations where GPS is blocked, typically this is within a structure. The project will design a set of mechanisms to facilitate Wi-Fi positioning, discover key principles to guide practical design, and develop advanced algorithms to push the performance limit to decimetre-level accuracy. The project will develop key fundamental technologies which are expected to promote innovative, practical, and cost-effective applications to local industry and service sectors and contribute to Australia's long-term economic growth.Read moreRead less