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
Classifying Internet traffic for security applications. As the internet traffic data exponentially increases every year, traffic classification has become a fundamental approach to the security of the Internet. This project aims to develop a set of novel techniques for internet traffic classification, which is fundamentally important to defend against the serious cyber-attacks and effectively minimise the damages. This project is significant as it can help to improve cyber security, which is ess ....Classifying Internet traffic for security applications. As the internet traffic data exponentially increases every year, traffic classification has become a fundamental approach to the security of the Internet. This project aims to develop a set of novel techniques for internet traffic classification, which is fundamentally important to defend against the serious cyber-attacks and effectively minimise the damages. This project is significant as it can help to improve cyber security, which is essential for the work and daily lives of the Australian people. Furthermore, the proposed models and techniques will be important for enhancing the protection of Australian critical infrastructures against malicious cyber-attacks.Read moreRead less
Sequential attribute-based encryption: new cryptographic framework, constructions and applications towards cloud security. The purpose of this project is to find niche and significant techniques to preserve the order of attributes in modern cryptography. Novel cryptographic techniques applicable to securing important areas, such as cloud computing and anonymous credential systems will be developed, which will lead to commercialisation.
Edge-Accelerated Deep Learning. Implementing deep learning (DL) applications usually requires a large amount of collected data and powerful computing resources in the cloud. However, this centralised approach has issues of high latency, large bandwidth usage, and possible privacy violation for many practical applications. Without properly addressing these issues, the wider application of DL in practice will seriously be hindered. This project aims to solve several key challenging problems in eff ....Edge-Accelerated Deep Learning. Implementing deep learning (DL) applications usually requires a large amount of collected data and powerful computing resources in the cloud. However, this centralised approach has issues of high latency, large bandwidth usage, and possible privacy violation for many practical applications. Without properly addressing these issues, the wider application of DL in practice will seriously be hindered. This project aims to solve several key challenging problems in effective deployment and efficient execution of DL applications in a distributed edge-computing environment. Several innovative edge-computing methods will be developed for DL training, inference and implementation to achieve high performance with low latency and enhanced privacy.Read moreRead less
Modelling and defence against malware propagation. As the internet has become vital to our day-to-day working and living, we are witnessing a remarkable upsurge in the incidents of malicious software or malware on it. This project aims to develop key technologies that can precisely model the malware propagation on the internet. The technologies will help develop effective defence against malware propagation at an early stage, with limited defence resources, so as to minimise the damage and provi ....Modelling and defence against malware propagation. As the internet has become vital to our day-to-day working and living, we are witnessing a remarkable upsurge in the incidents of malicious software or malware on it. This project aims to develop key technologies that can precisely model the malware propagation on the internet. The technologies will help develop effective defence against malware propagation at an early stage, with limited defence resources, so as to minimise the damage and provide a capability to identify and control malware spreaders. This project is significant as it can secure the internet that is essential to the daily work of Australian people, thus addresses a fundamental problem in safeguarding Australia by protecting our critical infrastructure.Read moreRead less
Flying networks: airborne sensing for environmental monitoring and disaster response. Airborne sensing technology is ideally suited to Australian geography and can be highly effective for monitoring disasters, surveillance, and precision agriculture. There are ample opportunities for local information technology companies and start-ups to create innovative airborne sensing applications for both the Australian and overseas markets.
Re-engineering internet timekeeping for scalability, accuracy and trust. This project aims to define and solve problems underpinning a secure and extensible system for network timekeeping, and implement and test a prototype under realistic conditions over the Internet. All computers incorporate a software clock, essential to software applications. A network is an inexpensive and convenient way to synchronise these clocks, but the Internet currently depends on an unreliable and insecure approach. ....Re-engineering internet timekeeping for scalability, accuracy and trust. This project aims to define and solve problems underpinning a secure and extensible system for network timekeeping, and implement and test a prototype under realistic conditions over the Internet. All computers incorporate a software clock, essential to software applications. A network is an inexpensive and convenient way to synchronise these clocks, but the Internet currently depends on an unreliable and insecure approach. The expected outcome will be trusted, accurate and reliable software clocks that support applications like cloud computing, billing systems and secure communications, which could become the timekeeping system for the Internet and the Internet of Things.Read moreRead less
In search of relevant things: A novel approach for image analysis. This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases ....In search of relevant things: A novel approach for image analysis. This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases in satellite and diagnostic imaging, respectively, among other applications. For the first time, the combination of how a computer analyses an image and how an expert interprets it will be used as a common language to enable machines to process visual information in a manner that mimics the way human brains do.Read moreRead less
Practical unified framework for secure e-consent mechanism for health records. This project is driven by modern applications of cryptography and network security and their applications in securing e-health by enabling secure Personal Health Records (PHRs), which will play an important role in the future healthcare industry.
Achieving security and privacy in radio frequency identification (RFID) with lightweight security technologies. Secure RFID technology to achieve reliable identification is essential for protecting critical information infrastructures. However, they are prone to security attacks due to difficulties in protecting RFID systems. This project will develop new lightweight security techniques to achieve practical security solutions for RFID.