# A High-Utility Differentially Private Mechanism for Space Information Networks
## 1 Introduction  
Revolutionary distributed communication infrastructures called Space Information Networks (SINs) are made up of satellites, stratospheric airships, unmanned aerial vehicles (UAV), and other platforms. SINs are distinct from multi-layered satellite networks. They are heterogeneous integrated information networks, including terrestrial Internet, Deep Space Network (DSN), Near-Earth Network (NEN), and satellite networks as the backbone. As a result, they have a variety of unique characteristics, such as heterogeneous network integration, dynamically changing network topology, extraordinarily long and variable propagation latency, asymmetrical forward and reverse link capacities, high bit error rate, intermittent link connectivity, lack of fixed communication resources, good network scalability, etc. Applications of SINs include satellite location, navigation, timing, and Internet access, in addition to satellite communication and remote sensing. SINs intend to achieve the networking and integration of space satellite systems, efficiently arrange the system's nodes via satellite-terrestrial and interstellar linkages, and increase the system's adaptability, mobility, and intelligence. Due to Space Information Networks' advantages such as long-distance message delivery, they have been applied to many scenarios, including emergency communications, marine operations, aircraft communications, specific military missions, and so on [1]. Space Information Networks have developed rapidly in recent years. For example, dozens of satellite internet emerge such as SpaceX's Starlink [2], the British government's OneWeb [3], and Amazon's Kuiper [4]. So far, the Starlink has more than 1700 active satellites, and it plants to increase its bandwidth from 150 Mbps to 300 Mbps at the end of 2021.  
Privacy issues emerge in the process of maintaining Space Information Networks. In particular, some information on Space Information Networks needs to be shared for the sake of operation and maintenance, but accurate information should not be shared for the sake of safety. For example, the location of satellites needs to be public so that the user knows which satellite and how many satellites are available. However, the accurate location of satellites needs to be private in case the adversary attacks satellites for particular reasons such as political issues. Similarly, other statistical information such as the average of power consumption, the number of active satellites, and so on also needs to be available for analysts so that they can analyze the operation of the satellites, but for safety reasons, these analysts do not have to know the information on an individual satellite.  
Differential privacy a technology that allows data analysis while keeping individuals' information private. In particular, differential privacy allows analysts to analyze statistic information such as average, frequency, and standard deviation, while it keeps the individuals' information private. In this paper, we design a differentially private mechanism for distributed communication systems such that entities of systems can communicate with each other while their privacy is protected. Although we take the Space Information Networks as an example, the proposed differentially private mechanism also can be applied into other distributed communication systems such as edge computing, ad-hoc networks, and so on.