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PRIVAaaS: privacy approach for a distributed cloud-based data analytics platforms

Authors:

Wagner Meira, Jr.Authors Info & Claims

CCGrid '17: Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

Pages 1108 - 1116

https://doi.org/10.1109/CCGRID.2017.136

Published: 14 May 2017 Publication History

Abstract

Data privacy is a key challenge that is exacerbated by Big Data storage and analytics processing requirements. Big Data and Cloud Computing are related and allow the users to access data from any device, making data privacy essential as the data sets are exposed through the web. Organizations care about data privacy as it directly affects the confidence that clients have that their personal data are safe. This paper presents a data privacy approach - PRIVAaaS - and its integration to the LEMONADE Web-based platform, developed to compose ETL (Extract, Transform, Load) process and Machine Learning workflows. The 3-level approach of PRIVAaaS, based on data anonymization policies, is implemented in a software toolkit that provides a set of libraries and tools which allows controlling and reducing data leakage in the context of Big Data processing.

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Cited By

Silva Jde França BRubira CCavalcante EDantas FBatista TPinto G(2020)Generating Trustworthiness Adaptation Plans Based on Quality Models for Cloud PlatformsProceedings of the 14th Brazilian Symposium on Software Components, Architectures, and Reuse10.1145/3425269.3425272(141-150)Online publication date: 19-Oct-2020
https://dl.acm.org/doi/10.1145/3425269.3425272

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cover image ACM Conferences

CCGrid '17: Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

May 2017

1167 pages

ISBN:9781509066100

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IEEE Press

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Published: 14 May 2017

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CCGrid '17: 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

May 14 - 17, 2017

Madrid, Spain

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Silva Jde França BRubira CCavalcante EDantas FBatista TPinto G(2020)Generating Trustworthiness Adaptation Plans Based on Quality Models for Cloud PlatformsProceedings of the 14th Brazilian Symposium on Software Components, Architectures, and Reuse10.1145/3425269.3425272(141-150)Online publication date: 19-Oct-2020
https://dl.acm.org/doi/10.1145/3425269.3425272

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