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BigPrivacy: Scaling privacy preservation for big data applications on cloud

Funding or Partner Organisation: Australian Research Council (ARC Discovery Projects)

Start year: 2017

Summary: This project aims to research scalable privacy preservation for big data applications on cloud. Privacy preservation is a major concern for big data applications on cloud, such as health data analysis where user privacy must be preserved. Scalable solutions can preserve privacy so that data analysis such as health diagnosis can be performed quickly. The expected deliverable is a unified scalable privacy preservation framework with associated algorithms and its prototype, which cloud systems can deploy for big data applications.

Publications:

Usman, M, Jan, MA, He, X & Chen, J 2020, 'A Survey on Big Multimedia Data Processing and Management in Smart Cities', ACM Computing Surveys, vol. 52, no. 3, pp. 1-29.
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Usman, M, Jan, MA, He, X & Chen, J 2019, 'P2DCA: A Privacy-Preserving-Based Data Collection and Analysis Framework for IoMT Applications', IEEE Journal on Selected Areas in Communications, vol. 37, no. 6, pp. 1222-1230.
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Keywords: Big Data, Privacy Preservation, Scalability, Data Science

FOR Codes: Database Management, Internet Hosting Services (incl. Application Hosting Services), Information Processing Services (incl. Data Entry and Capture), Database systems, Information systems, technologies and services not elsewhere classified