基于学习误差的加密方案用于动态控制器，用于异常检测的残差信号披露
A Learning With Errors based encryption scheme for dynamic controllers that discloses residue signal for anomaly detection
AI总结：
本文提出了一种基于学习误差的加密方案，用于动态控制器，能够在不泄露秘密密钥的情况下自动披露残差信号以检测异常，同时保持其他信号的隐私。
摘要：
尽管加密控制系统可以确保私有数据的保密性，但没有秘密密钥的情况下检测异常具有挑战性，因为所有信号都保持加密。为了解决这个问题，我们提出了一种适用于动态控制器的同态加密方案，该方案能够自动披露残差信号以进行异常检测，同时保持其他信号的隐私。为此，我们表征了在有限整数域上加密动态系统的零动力学，并将其纳入基于学习误差（LWE）的方案中。然后，我们提出了一种方法，利用披露的残差信号在加密数据上实现动态控制器，即使在状态矩阵不是整数时也不需要重新加密。
英文摘要：
Although encrypted control systems ensure confidentiality of private data, it is challenging to detect anomalies without the secret key as all signals remain encrypted. To address this issue, we propose a homomorphic encryption scheme for dynamic controllers that automatically discloses the residue signal for anomaly detection, while keeping all other signals private. To this end, we characterize the zero-dynamics of an encrypted dynamic system over a finite field of integers and incorporate it into a Learning With Errors (LWE) based scheme. We then present a method to further utilize the disclosed residue signal for implementing dynamic controllers over encrypted data, which does not involve re-encryption even when they have non-integer state matrices.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
