# Augmented Reality and the Digital Twin: State-of-the-Art and Perspectives for Cybersecurity
## 1 Introduction  
The Digital Twin (DT) is a key enabling technology in the digital transformation of industries to digitalize physical assets. Over the past few years, the demand for DT solutions increased significantly, with its potential advantages attracting attention from aerospace to healthcare. The digital representation of physical assets often allows pursuing new businesses opportunities or gaining highly relevant new insights. Therefore, the DT market is expected to increase its volume from an estimated 3.1 billion USD in 2020 to 48.2 billion USD by 2026 [1]. A contrast to the relatively new DT trend is the concept of Augmented Reality (AR), which has been around for several decades [2]. However, it is experiencing new attention since, for the first time, respective technology is affordable and capable of leveraging AR's full potential [3]. Today, the available hardware to realize AR applications allows implementing new ways of human-machine interaction and information visualization in various use cases. Both concepts, DT and AR, play a significant role in the currently ongoing industrial revolution [4, 5]. Most interestingly, DT and AR are highly complementary concepts in this context. While the DT allows representing physical assets in the digital space, AR enables augmenting the physical space with digital information. Therefore, applying these two concepts in combination unlocks a new way of human-machine interaction and, especially, a new way of situational awareness [6]. They help to realize a seamless integration of users into the cyber-physical space. Thus, users' situational awareness is not limited to a digital visualization of relevant data but can be directly contextualized with the respective real-world objects. Digital data and physical data are blended, allowing users to be really aware of the situation regarding cyberspace-related aspects, as well as regarding the physical world [7]. In recent years, research has picked up on the combination of AR and DT, and a significant amount of work has been done to explore its possibilities. Nevertheless, very little work has been done to unleash the potential of applying AR combined with a DT in the cybersecurity context. While the DT concept is becoming more prevalent in security research, its application is mainly limited to simulating attacks on physical assets or similar one-dimensional use cases [4]. However, the rise of Cyber-Physical Systems (CPS) and the Internet of Things (IoT), with an accompanying increase of DT applications, require using DTs the DT for cybersecurity, as well as securing the DTs themselves [8]. Although many automated approaches for detecting and preventing security incidents exist, experts remain essential to make final decisions and interpret results. In addition to their domain knowledge, situational awareness plays an essential role in this decision-making process [9]. The use of AR for DT offers excellent opportunities to sharpen the situational awareness of security professionals through the direct connection of real-world objects with cyberspace. However, security research currently does not seem to be fully aware of this potential and is, thus, lacking a clear vision and perspective to leverage the potential slumbering in the combined-arms approach of AR and DT. With our work, we make a first two-fold contribution to this problem. To develop a tenable perspective on the combined use of AR and DT in cybersecurity, we first capture the current state of research on the AR/DT combination through a structured literature review (SLR). In the second part of the paper, we leverage the insights gained in the SLR to develop a vision of how the AR/DT combination can contribute to improving an enterprise's security posture. The remainder of this work is structured as follows. Section 2 briefly introduces background knowledge on the concepts of AR and DT. Throughout Section 3, we describe a structured literature analysis regarding the applied methodology, as well as both relevant quantitative and qualitative results.