An Improved Bound for Security in an Identity Disclosure Problem

TL;DR

This paper improves the theoretical bounds on privacy protection in identity disclosure, showing that security levels can be extended to any probability threshold under certain conditions.

Contribution

It extends previous work by Nayak et al. on obfuscation methods, providing conditions for achieving security for all probability thresholds.

Findings

Security bounds can be extended to any probability threshold 0 < t < 1.

Conditions are identified under which improved security guarantees are possible.

Theoretical analysis enhances understanding of privacy protection limits.

Abstract

Identity disclosure of an individual from a released data is a matter of concern especially if it belongs to a category with low frequency in the data-set. Nayak et al. (2016) discussed this problem vividly in a census report and suggested a method of obfuscation, which would ensure that the probability of correctly identifying a unit from released data, would not exceed t for some 1/3 < t < 1. However, we observe that for the above method the level of security could be extended under certain conditions. In this paper, we discuss some conditions under which one can achieve a security for any 0 < t < 1.