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
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
Spectrum after Scarcity: Rethinking Radiofrequency Management. Radiofrequency spectrum is the critical input that enables wireless communication. Existing spectrum management tools were constructed to deal with scarcity. This project aims to reconceptualise spectrum management as technological developments reduce scarcity. In four overlapping stages, an international research team aims to investigate the regulatory implications of emerging technologies that share spectrum; conduct fifteen case s ....Spectrum after Scarcity: Rethinking Radiofrequency Management. Radiofrequency spectrum is the critical input that enables wireless communication. Existing spectrum management tools were constructed to deal with scarcity. This project aims to reconceptualise spectrum management as technological developments reduce scarcity. In four overlapping stages, an international research team aims to investigate the regulatory implications of emerging technologies that share spectrum; conduct fifteen case studies of spectrum 'refarming' around the world over the last two decades, including secondary trading, public reallocations and renewals; explore models for dynamic integration of spectrum sharing and refarming; and publish an accessible intellectual history of a unique resource.Read moreRead less
Managing private location data in a mobile and networked world: getting the balance right. Location based data are transforming the mobile service industry and this project will develop novel approaches to safeguard the location privacy of mobile individuals. This will facilitate the development of privacy-aware services which can be used for real time traffic monitoring, care for the elderly and smartphone enabled location services.
Low-Complexity Capacity-Scalable Multiple Antenna Wireless Communications. The project aims to develop innovative solutions for low-complexity, capacity-scalable multiple antenna wireless communications, in order to meet future data rate requirements whilst maintaining a practical system at a sustainable cost. By leveraging delay-Doppler domain channel properties and geometric reciprocity, pragmatic transceiver technologies and innovative delay-Doppler domain signal processing algorithms for cha ....Low-Complexity Capacity-Scalable Multiple Antenna Wireless Communications. The project aims to develop innovative solutions for low-complexity, capacity-scalable multiple antenna wireless communications, in order to meet future data rate requirements whilst maintaining a practical system at a sustainable cost. By leveraging delay-Doppler domain channel properties and geometric reciprocity, pragmatic transceiver technologies and innovative delay-Doppler domain signal processing algorithms for channel prediction and multi-user transmissions will be developed. The outcomes of the project are expected to significantly improve users' data rates with low system complexity and reduced signalling overhead for future wireless communications.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
Tools and models for measuring and predicting growth in internet addressing and routing complexity. We analyse patterns in the allocation and actual use of Internet Protocol version 4 (IPv4) addresses to predict the technical and market pressures for deployment of IPv6. The utilisation models will help evaluate the potential for emerging markets in scarce IPv4 address prefixes to increase costs to the end-users of Australia's future national broadband network.
Discovery Early Career Researcher Award - Grant ID: DE210101497
Funder
Australian Research Council
Funding Amount
$427,455.00
Summary
Structured Codes: Harnessing Interference to Improve Communication Networks. Interference occurs when a device involuntarily receives signals from unintended transmitters. Interference is the biggest challenge in modern large-scale communication networks. In contrast to conventional wisdom that avoids interference, this project aims to harness interference for its advantage. It will view interference as a form of computation that can be exploited advantageously using structured codes. Developing ....Structured Codes: Harnessing Interference to Improve Communication Networks. Interference occurs when a device involuntarily receives signals from unintended transmitters. Interference is the biggest challenge in modern large-scale communication networks. In contrast to conventional wisdom that avoids interference, this project aims to harness interference for its advantage. It will view interference as a form of computation that can be exploited advantageously using structured codes. Developing theory and novel coding techniques, this project expects to deepen our understanding of interference, and significantly increase the network bandwidth efficiency. Expected outcomes will benefit a wide range of applications such as next-generation mobile systems, sensor networks, and cyber-physical systems.Read moreRead less
The Game of Being Mobile: A study of mobile gaming cultures. This is the first Australian study to examine the social uses of mobile gaming. Smartphones have put location-based and social media games in the hands of mobile users worldwide. Through ethnographic methods, this study will explore how mobile game consumption is reflecting, and being shaped by, complex social and technological practices integral to contemporary life.
Coordinated non-coherent wireless for safe and secure networking. Distributed wireless networks have the potential to serve simultaneous users streaming high-definition video, no dead zones, no interference among users and no reduction in data rate as more users are added. This project will provide a solution to the current limitations of distributed wireless networks aiming at user safety and privacy.