Distributed data sharing in dynamic networks is ubiquitous. It raises the concern that the private information of dynamic networks could be leaked when data receivers are malicious or communication channels are insecure. In this paper, we propose to intentionally perturb the inputs and outputs of a linear dynamic system to protect the privacy of target initial states and inputs from released outputs. We formulate the problem of perturbation design as an optimization problem which minimizes the cost caused by the added perturbations while maintaining system controllability and ensuring the privacy. We analyze the computational complexity of the formulated optimization problem. To minimize the ${\ell }_0$ and ${\ell }_2$ norms of the added perturbations, we derive their convex relaxations which can be efficiently solved. The efficacy of the proposed techniques is verified by a case study on a heating, ventilation, and air conditioning system.

动态网络中的分布式数据共享无处不在。当数据接收者是恶意的或通信通道不安全时，动态网络的私有信息可能会泄漏，这引起了人们的关注。在本文中，我们建议有意地扰动线性动态系统的输入和输出，以保护目标初始状态和输入与释放输出的私密性。我们将扰动设计问题表述为一个优化问题，该问题可以在保持系统可控制性和确保隐私的同时，最大限度地减少由增加的扰动引起的成本。我们分析制定的优化问题的计算复杂性。尽量减少${\ell }_0$ 和 ${\ell }_2$附加扰动的范数，我们得出它们的凸松弛，可以有效地解决。通过对加热，通风和空调系统进行的案例研究，验证了所提出技术的有效性。