MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) ne ....MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) new methods for susceptibility diagnosis, 3) new defences that leverage privacy and utility. Data-oriented services are estimated to be valuable assets in the future. These techniques can help Australia gain cutting edge advantage in machine learning security and privacy and protect its intellectual property on these services.Read moreRead less
Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while pres ....Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while preserving the data privacy. These tools should provide significant benefits to the privacy of cloud users, as well as financial and reputation benefits to the IT industry, by significantly reducing the likelihood of massive user data privacy breaches in the event of a cyber-hacking attack on the cloud server.Read moreRead less
Developing A Smart Farming Oriented Secure Data Infrastructure. Smart farming is the future of agriculture. However, recently the Federal Bureau of Investigation has issued a
warning that the lack of data privacy and cyber security mechanisms in the field runs a high risk of disaster. This
project aims to establish an innovative secure data infrastructure for smart farming including secure and automated smart farming supply-chain management. The deliverables of this project will include the cutt ....Developing A Smart Farming Oriented Secure Data Infrastructure. Smart farming is the future of agriculture. However, recently the Federal Bureau of Investigation has issued a
warning that the lack of data privacy and cyber security mechanisms in the field runs a high risk of disaster. This
project aims to establish an innovative secure data infrastructure for smart farming including secure and automated smart farming supply-chain management. The deliverables of this project will include the cutting-edge Blockchain based secure IoT data management and privacy-preserving smart contracts for smart farming supply-chain management. This data infrastructure will be the first of its kind which will lay a solid foundation for smart farming technology.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100595
Funder
Australian Research Council
Funding Amount
$416,400.00
Summary
Efficient privacy-preserving proofs for secure e-government and e-voting. Electronic systems are becoming increasingly widespread and crucial to social and economic wellbeing. This project aims to ensure that e-government, e-health, e-commerce and e-voting are secure and trustworthy by inventing new ways to verify these systems without infringing privacy. This project expects to use innovative techniques from cryptography to support development of trustworthy systems. Expected outcomes of this p ....Efficient privacy-preserving proofs for secure e-government and e-voting. Electronic systems are becoming increasingly widespread and crucial to social and economic wellbeing. This project aims to ensure that e-government, e-health, e-commerce and e-voting are secure and trustworthy by inventing new ways to verify these systems without infringing privacy. This project expects to use innovative techniques from cryptography to support development of trustworthy systems. Expected outcomes of this project include better support for organisations to build trustworthy systems that will maximise benefit to Australian business and society. This should provide significant commercial, reputational, and societal benefits by avoiding disruptions to the organisations and their clients if and when they are attacked. Read moreRead less
Verified concurrent memory management on modern processors. This project aims to formally verify automatic memory managers in the presence of concurrency and the weakly ordered memory of modern processors. A new framework for verifying memory managers, reusable for a wide range of managed programming languages, target hardware, policies, and algorithms will be developed. Expected technical outcomes include improved techniques to ensure trustworthiness of the foundations on which critical softwar ....Verified concurrent memory management on modern processors. This project aims to formally verify automatic memory managers in the presence of concurrency and the weakly ordered memory of modern processors. A new framework for verifying memory managers, reusable for a wide range of managed programming languages, target hardware, policies, and algorithms will be developed. Expected technical outcomes include improved techniques to ensure trustworthiness of the foundations on which critical software infrastructures are built. This will significantly enhance the security of public and private cyber assets, and deliver applications that are more robust and trustworthy, across a range of critical infrastructure such as transportation, communication, energy and defence.Read moreRead less
DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting th ....DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting the attractiveness and evolving the system. The project expects to advance deep learning and yield novel DeepHoney technologies with associated publications and open-source software. This should benefit science, society, and the economy by building the next generation of active cyber defence systems. Read moreRead less
Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coord ....Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coordinated cyber-attacks that will potentially lead to catastrophic cascaded failures; and develop new solutions in detecting the false data-injection attacks that are conventionally considered as unobservable. This project will provide the benefit of enhancing our national critical infrastructure's security.Read moreRead less
Privacy-preserving Biometrics based Authentication and Security. Password based authentication systems cannot verify genuine users. Biometric authentication can address this issue. However, the booming IoT applications and cloud computing require that the biometric authentication must be conducted in the privacy-protected setting in order to comply with privacy protection legal regulations. Latest reports show that current biometric authentication systems, under protected setting, exhibit poor ....Privacy-preserving Biometrics based Authentication and Security. Password based authentication systems cannot verify genuine users. Biometric authentication can address this issue. However, the booming IoT applications and cloud computing require that the biometric authentication must be conducted in the privacy-protected setting in order to comply with privacy protection legal regulations. Latest reports show that current biometric authentication systems, under protected setting, exhibit poor authentication performance, which is not commercially applicable. This project aims to investigate innovative solutions to this issue. The intended deliverables will include deep learning based biometric feature extractor, cancellable biometrics and cloud oriented biometrics security protocols. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100863
Funder
Australian Research Council
Funding Amount
$405,398.00
Summary
Privacy Coupling: When Your Personal Devices Betray You. This project aims to propose novel privacy preserving schemes that can protect the privacy of individuals in the era of Internet of things and machine learning. In the recent years, most Australian organizations have been a target of privacy and cybersecurity attacks, affecting their data and network systems. The expected outcomes of this project are privacy preserving schemes that can prevent attackers from compromising the private inform ....Privacy Coupling: When Your Personal Devices Betray You. This project aims to propose novel privacy preserving schemes that can protect the privacy of individuals in the era of Internet of things and machine learning. In the recent years, most Australian organizations have been a target of privacy and cybersecurity attacks, affecting their data and network systems. The expected outcomes of this project are privacy preserving schemes that can prevent attackers from compromising the private information of individuals in IoT and machine learning services, and thus significantly improve the protection against cybersecurity attacks. Significant benefits in social wellbeing and security are expected for all industry, government, and service sectors that collect data about people.Read moreRead less