Utilizing Noise Addition for Data Privacy, an Overview

Abstract

The internet is increasingly becoming a standard for both the production and consumption of data while at the same time cyber-crime involving the theft of private data is growing. Therefore in efforts to securely transact in data, privacy and security concerns must be taken into account to ensure that the confidentiality of individuals and entities involved is not compromised, and that the data published is compliant to privacy laws. In this paper, we take a look at noise addition as one of the data privacy providing techniques. Our endeavor in this overview is to give a foundational perspective on noise addition data privacy techniques, provide statistical consideration for noise addition techniques and look at the current state of the art in the field, while outlining future areas of research.

6 pages, 3 Figures

References in corpus (2)

• Differential Privacy: on the trade-off between Utility and Information Leakage
• A Noise Addition Scheme in Decision Tree for Privacy Preserving Data Mining

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• A Survey of Privacy Vulnerabilities of Mobile Device Sensors
• You can't always get what you want: towards user-controlled privacy on Android
• Privacy Preserving Techniques Applied to CPNI Data: Analysis and Recommendations
• A Review of Privacy Essentials for Confidential Mobile Data Transactions
• Data Masking with Privacy Guarantees
• An Investigation of Data Privacy and Utility Preservation using KNN Classification as a Gauge