CRSep 16, 2013

Utilizing Noise Addition for Data Privacy, an Overview

arXiv:1309.3958v185 citations
Originality Synthesis-oriented
AI Analysis

It reviews existing methods for data privacy, making it incremental as it does not propose novel solutions.

This paper provides an overview of noise addition techniques for data privacy, addressing the need for secure data transactions in the face of growing cyber-crime, but does not present new experimental results or concrete numbers.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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