Symmetries and Isomorphisms for Privacy in Control Over the Cloud

Cloud computing platforms are being increasingly used for closing feedback control loops, especially when computationally expensive algorithms, such as model-predictive control, to optimize performance. Outsourcing of algorithms entails an exchange data between the system and cloud and, naturally, raises concerns about privacy system's (e.g., state trajectory objective). Moreover, any attempt at enforcing needs add minimal computational overhead avoid degrading In this article, we propose several transformation-based methods privacy. We also quantify amount provided discuss how much is lost adversary has access side knowledge. address three different scenarios: 1) no knowledge controlled; 2) knows what sensors actuators employs but not dynamics; 3) dynamics, its sensors, actuators. all these scenarios, proposed allow over without compromising private information (which considered depends on scenario).