Biblio

The space environment is currently undergoing a substantial change and many new entrants to the market are deploying devices, satellites and systems in space; this evolution has been termed as NewSpace. The change is complicated by technological developments such as deploying machine learning based autonomous space systems and the Internet of Space Things (IoST). In the IoST, space systems will rely on satellite-to-x communication and interactions with wider aspects of the ground segment to a greater degree than existing systems. Such developments will inevitably lead to a change in the cyber security threat landscape of space systems. Inevitably, there will be a greater number of attack vectors for adversaries to exploit, and previously infeasible threats can be realised, and thus require mitigation. In this paper, we present a reference architecture (RA) that can be used to abstractly model in situ applications of this new space landscape. The RA specifies high-level system components and their interactions. By instantiating the RA for two scenarios we demonstrate how to analyse the attack surface using attack trees.

Source location privacy (SLP) is becoming an important property for a large class of security-critical wireless sensor network applications such as monitoring and tracking. Much of the previous work on SLP have focused on the development of various protocols to enhance the level of SLP imparted to the network, under various attacker models and other conditions. Others works have focused on analysing the level of SLP being imparted by a specific protocol. In this paper, we focus on deconstructing routing-based SLP protocols to enable a better understanding of their structure. We argue that the SLP-aware routing protocols can be classified into two main categories, namely (i) spatial and (ii) temporal. Based on this, we show that there are three important components, namely (i) decoy selection, (ii) use and routing of control messages and (iii) use and routing of decoy messages. The decoy selection technique imparts the spatial or temporal property of SLP-aware routing. We show the viability of the framework through the construction of well-known SLP-aware routing protocols using the identified components.