# Single-Component Privacy Guarantees in Helper Data Systems and Sparse Coding with Ambiguation

## TL;DR

This paper examines privacy guarantees in helper data systems and sparse coding, focusing on protecting specific binary properties of biometric feature vectors against leakage.

## Contribution

It introduces an analysis of privacy leakage regarding binary properties in biometric template protection methods and discusses parameter settings for enhanced privacy.

## Key findings

- Both approaches can protect sensitive binary variables.
- System parameters significantly influence privacy leakage.
- The study highlights overlooked privacy aspects in biometric systems.

## Abstract

We investigate the privacy of two approaches to (biometric) template protection: Helper Data Systems and Sparse Ternary Coding with Ambiguization. In particular, we focus on a privacy property that is often overlooked, namely how much leakage exists about one specific binary property of one component of the feature vector. This property is e.g. the sign or an indicator that a threshold is exceeded. We provide evidence that both approaches are able to protect such sensitive binary variables, and discuss how system parameters need to be set.