Using Noisy Binary Search for Differentially Private Anomaly Detection.

In this paper, we study differential privacy in noisy search. This problem is connected to noisy group testing: the goal is to find a defective or anomalous item within a group using only aggregate group queries, not individual queries. Differentially private noisy group testing has the potential to be used for anomaly detection in a way that provides differential privacy to the non-anomalous individuals while still helping to allow the anomalous individuals to be located. To do this, we introduce the notion of anomaly-restricted differential privacy. We then show that noisy group testing can be used to satisfy anomaly-restricted differential privacy while still narrowing down the location of the anomalous samples, and evaluate our approach experimentally.