Building an Anonymization Pipeline: Creating Safe Data

by Luk Arbuckle, Khaled El Emam

How can you use data in a way that protects individual privacy but still provides useful and meaningful analytics? With this practical book, data architects and engineers will learn how to establish and integrate secure, repeatable anonymization processes into their data flows and analytics in a sustainable manner. Luk Arbuckle and Khaled El Emam from Privacy Analytics explore end-to-end solutions for anonymizing device and IoT data, based on collection models and use cases that address real business needs. These examples come from some of the most demanding data environments, such as healthcare, using approaches that have withstood the test of time.

Genres: Technology

164 pages, Paperback

Published May 19, 2020

Reviews

[Александр Гидревич · Rating 3 out of 5]

The book directed to be solid basis for theoretical presentation of terminology and concepts behind anonymization pipeline. Good for first chapter of your PhD dissertation so five stars here. But from engineering (aka tools and RL examples) point of view book can be easily omitted.