Daniel J. Spencer

Quantum sensing is a promising technology capable of demonstrating clear advantage over comparable classical techniques for precise measurement. One application of quantum sensing is in function estimation, which can be done using a network of entangled quantum sensors, allowing for measurements with greater optimal sensitivity than unentangled sensing protocols. Since quantum sensor networks will likely be used to measure data that should remain private (e.g., biomedical data), it is imperative that these protocols include a cryptographic mechanism to hide sensitive information. In this work, we show that entangled sensor networks are vulnerable to differential attacks. To mitigate these attacks, we introduce secure sensing protocols based on differential privacy. We reconcile Heisenberg-limited scaling and differential privacy and introduce several protocols achieving varying balances between the two. We show that our protocols are resilient to attacks by quantum adversaries and we find advantages in the privacy-utility trade-off when using quantum resources.