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

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