Data Privacy Protection in Wireless Sensor Networks. This project aims to explore a comprehensive solution for the protection of privacy-sensitive data in wireless sensor networks (WSNs) that are vulnerable to hacking. The project expects to use an innovative approach involving multiple data servers to protect sensor data privacy from data collection to data access and analysis. Expected outcomes of this project include new security and privacy models for WSNs in the setting of multiple servers, ....Data Privacy Protection in Wireless Sensor Networks. This project aims to explore a comprehensive solution for the protection of privacy-sensitive data in wireless sensor networks (WSNs) that are vulnerable to hacking. The project expects to use an innovative approach involving multiple data servers to protect sensor data privacy from data collection to data access and analysis. Expected outcomes of this project include new security and privacy models for WSNs in the setting of multiple servers, new secure protocols, privacy-preserving access control and data analysis protocols, and a prototype of a privacy-preserving WSN system. This should provide significant benefits, such as improved security of sensitive data in the healthcare system, military, utilities and telecommunications.
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Privacy-Preserving Collaborative Analytics on Sensitive Data. This project aims to develop efficient solutions that allow multiple institutes to carry out collaborative analytics on aggregated data without revealing their sensitive data to each other. The project expects to remedy acute privacy concerns when institutes share sensitive data across boundaries for collective insights. The expected outcomes include a hybrid trust model with distributed trusts to provide malicious security guarantees ....Privacy-Preserving Collaborative Analytics on Sensitive Data. This project aims to develop efficient solutions that allow multiple institutes to carry out collaborative analytics on aggregated data without revealing their sensitive data to each other. The project expects to remedy acute privacy concerns when institutes share sensitive data across boundaries for collective insights. The expected outcomes include a hybrid trust model with distributed trusts to provide malicious security guarantees, lightweight privacy-enhancing techniques to express rich analytical functionalities, and a system platform for real-world applications. This should provide significant benefits such as facilitating industries to safeguard their customers' data and uplift their businesses in a secure and trustworthy fashion.Read moreRead less