Apriori_based_Anonymization is a counting tree based data anonymization algorithm for set-valued dataset, proposed by Manolis Terrovitis in his papers[1-2]. Terrovitis gave the pseudocode in his papers, the source code(C++ implement) is not available.

This repository is an open source python implement for Apriori_based_Anonymization. I implement this algorithm in python for further study.

Researches on data privacy have lasted for more than ten years, lots of great papers have been published. However, only a few open source projects are available on Internet [3-4], most open source projects are using algorithms proposed before 2004! Fewer projects have been used in real life. Worse more, most people even don't hear about it. Such a tragedy!

I decided to make some effort. Hoping these open source repositories can help researchers and developers on data privacy (privacy preserving data publishing).

[1] Terrovitis, M.; Mamoulis, N. & Kalnis, P. Privacy-preserving anonymization of set-valued data Proc. VLDB Endow., VLDB Endowment, 2008, 1, 115-125

[2] Terrovitis, M.; Mamoulis, N. & Kalnis, P. Local and global recoding methods for anonymizing set-valued data The VLDB Journal, Springer-Verlag New York, Inc., 2011, 20, 83-106

[3] UTD Anonymization Toolbox

[4] ARX- Powerful Data Anonymization