A toolkit converts sensitive data/private data to anonymous data/ privacy free data. It includes de-identification verification and risk evaluation. A deep learning methodology also builds inside to generate synthetic data that for data exchanging or sharing.
Applications & Benefits
Data privacy issues becomes a prior consideration for big data or AI applications. As GDPR applied at May 2018, the restriction for personal data came rigorous and clear. While collecting data for AIoT、AI、Big data analytic application, the personal data should be well managed for further usage. A de-identification technology(also called Privacy Enhancing Technology, PET) plays the important role for data exchange 、sharing or release/publishing.
CITC provide a set of toolkits for de-identification processing, which includes (1) data generalization, (2) data tokenization, (3) parallelized engine on big data platform for K-anonymity algorithm, (4)anonymous data generation/ synthesize, (5)data risk and utility analysis. These toolkits can be applied to open data processing、data release/ publishing、Fintec/ finance applications and also support the de-id requirements of GDPR.
The advantages of CITC’s de-id solution toolkits are both consider the private、risk and data utility to fulfill the privacy requirement in different domains and regions. It can follow privacy by design (PbD) issues to integrate with database system、big data platform…etc.. This solution was honored by the Taiwan BSMI as title of “The Advance Technology of Standardization” at 2016.