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Personal Privacy Preserving Analytics

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The Personal Privacy Preserving Analytics (P-PPA) module has the goal of allowing data analysts and stakeholders to extract useful information from the raw data while preserving the privacy of the users whose data is in the datasets. It leverages concepts like Differential Privacy and K-Anonymity so that data can be processed and shared while guaranteeing privacy for the users.

The Personal Privacy Preserving Analytics (P-PPA) module has the goal of allowing data analysts and stakeholders to extract useful information from the raw data while preserving the privacy of the users whose data is in the datasets. It leverages concepts like Differential Privacy and K-Anonymity so that data can be processed and shared while guaranteeing privacy for the users.

P-PPA includes a set of functionalities that allow perform data operations preserving the major privacy properties: k-anonymity, z-anonymity, differential privacy. P-PPA is capable to handle different sources of data inputs, that define which kind of privacy property is called into account: we have design solutions for tabular and batch stream, handled with PostgreSQL, MongoDB, and CSV modules, and live stream data.