"Novel System Prevents Personal Metadata Leakage From Online Behavior for Privacy Protection"
According to researchers at the City University of Hong Kong (CityU), preserving privacy is the most difficult aspect of data collection. Even if the data is encrypted, metadata, such as the online behavior of users, can result in identity exposure. Therefore, a research team at CityU has developed "Vizard," a metadata-hiding analytic system that enables data owners to securely define their data authorization and control who can use their data. The Vizard system has potential applications in multiple areas, such as precision medical research. The team used a cryptographic tool called "Distributed Point Function" (DPF) to design Vizard as a metadata-protected data collection and analysis platform. DPF is a building block that supports secure/encrypted computations, which can be used to retrieve data anonymously during computation. According to Wang Cong, a Professor in the Department of Computer Science at CityU, the team developed the Vizard system with stream-specific pre-processing, encryption, and throughput enhancement methods based on DPF. This article continues to discuss the Vizard metadata-hiding analytic system developed by researchers at CityU.