With the recent dramatic increase in performance of artificial intelligence and related computing systems, together with advanced sensing, connectivity, and technological platforms, autonomous systems are poised to enter many application domains such as transportation and manufacturing. As autonomy increases, the risks of cybersecurity threats are equally rising, requiring the development of sophisticated methods on all layers of autonomous systems architectures. Therefore, this paper systematically introduces cybersecurity challenges ranging from the physical layer to the system of systems layer defining the collaboration of autonomous systems. Without loss of generality, autonomous vehicles are used to highlight current developments, illustrating which efforts are necessary to achieve secure and safe autonomous systems. Our discussions are comprehensively highlighting which research domains require further investigation and offer promising opportunities to contribute to mitigating cybersecurity challenges of autonomous systems.

In this work, we demonstrate the possibility of spoofing a GNSS receiver to arbitrary locations without modifying the navigation messages. Due to increasing spoofing threats, Galileo and GPS are evaluating broadcast authentication techniques to validate the integrity of navigation messages. Prior work required an adversary to record the GNSS signals at the intended spoofed location and relay them to the victim receiver. Our attack demonstrates the ability of an adversary to receive signals close to the victim receiver and in real-time generate spoofing signals for an arbitrary location without modifying the navigation message contents. We exploit the essential common reception and transmission time method used to estimate pseudorange in GNSS receivers, thereby potentially rendering any cryptographic authentication useless. We build a proof-of-concept real-time spoofer capable of receiving authenticated GNSS signals and generating spoofing signals for any arbitrary location and motion without requiring any high-speed communication networks or modifying the message contents. Our evaluations show that it is possible to spoof a victim receiver to locations as far as 4000~km away from the actual location and with any dynamic motion path. This work further highlights the fundamental limitations in securing a broadcast signaling-based localization system even if all communications are cryptographically protected.

Today, an increasing number of applications rely on location and proximity information to deliver services. With the introduction of Wi-Fi Fine Timing Measurement (FTM) in the IEEE 802.11-2016 standard, Wi-Fi derived location and proximity information will play a key role in many safety- and security-critical applications. For example, Wi-Fi FTM is adopted in Wi-Fi Aware where it enables geo-fencing and mobile identification. In this paper, we perform the first security analysis of Wi-Fi FTM and analyze its security guarantees across the logical and physical layers. We find various weaknesses that enable an attacker to introduce distance reductions and enlargements to any arbitrary attacker-chosen value, requiring commodity hardware only. We perform an evaluation using commercial access points, smartphones, and off-the-shelf Wi-Fi cards, and show that an attacker can manipulate distances with meter-level precision. Furthermore, we highlight the distance manipulation attacks which are independent of any higher-layer cryptographic protection, exposing fundamental limitations to achieving secure distance measurements in the current standard. Finally, we present security recommendations for the design and implementation of Wi-Fi FTM and next-generation positioning protocols.

IEEE 802.15.4z, a standard for Ultra-Wide Band (UWB) secure distance measurement, was adopted in 2020 and the chips that implement this standard are already deployed in mobile phones and in the automotive industry (for Passive Keyless Entry and Start). The standard specifies two different modes---LRP and HRP. Whereas the security of LRP mode has been analyzed, there is no publicly available security analysis of the HRP mode, which is used in different chips like NXP Trimension SR150/SR040, Samsung smartphones, and U1 chip deployed in Apple iPhones.

Secure distance measurement and therefore secure Time-of-Arrival (ToA) measurement is critical for applications such as contactless payments, passive-keyless entry and start systems, and navigation systems. This paper initiates the study of Message Time of Arrival Codes (MTACs) and their security. MTACs represent a core primitive in the construction of systems for secure ToA measurement. By surfacing MTACs in this way, we are able for the first time to formally define the security requirements of physical-layer measures that protect ToA measurement systems against attacks. Our viewpoint also enables us to provide a unified presentation of existing MTACs (such as those proposed in distance-bounding protocols and in a secure distance measurement standard) and to propose basic principles for protecting ToA measurement systems against attacks that remain unaddressed by existing mechanisms. We also use our perspective to systematically explore the tradeoffs between security and performance that apply to all signal modulation techniques enabling ToA measurements.

A key challenge in participatory sensing systems has been the design of incentive mechanisms that motivate individuals to contribute data to consuming applications. Emerging trends in urban development and smart city planning indicate the use of citizen reports to gather insights and identify areas for transformation. Consumers of these reports (e.g. city agencies) typically associate non-uniform utility (or values) to different reports based on the spatio-temporal context of the reports. For example, a report indicating traffic congestion near an airport, in early morning hours, would tend to have much higher utility than a similar report from a sparse residential area. In such cases, the design of an incentive mechanism must motivate participants, via appropriate rewards (or payments), to provide higher utility reports when compared to less valued ones. The main challenge in designing such an incentive scheme is two-fold: (i) lack of prior knowledge of participants in terms of their availability (i.e. who are in the vicinity) and reporting behaviour (i.e. what are the rewards expected); and (ii) minimizing payments to the reporters while ensuring that the desired number of reports are collected. In this paper, we propose STOC-PISCES, an algorithm that guarantees a stochastic optimal solution in the generalized setting of an unknown set of participants, with non-deterministic availabilities and stochastically rational reporting behaviour. The superior performance of STOC-PISCES in experimental settings, based on real-world data, endorses its adoption as an incentive strategy in participatory sensing applications like smart city management.

While the density of access points in enterprise settings has increased, the sharing of the spatial resource amongst links in 802.11 wireless local area networks remains inefficient. Conservative mechanisms based on a static carrier sense range (CSR) are used and are designed to avoid occurrence of interfering transmissions. Even when the CSR is adapted to allow interfering transmissions, it is with the goal of increasing spatial reuse, which may not translate to a larger network throughput. We formulate the network throughput optimization problem, which is to decide which links in a network must share in space (transmit data simultaneously) such that the network throughput is maximized. Links share in space by piggybacking on data transmission opportunities seized by another link using RTS/CTS as specified in the distributed coordination function (DCF) of 802.11. Sharing in space increases interference and hence reduces the PHY rate at which a link can send data. It also increases the opportunities a link gets to transmit data, however. The optimization problem is NP hard. A relaxation of the problem gives an upper bound on network throughput. We propose computationally feasible algorithms that achieve a significant percentage of the upper bound. Our network modeling and evaluation is restricted to 802.11 networks in which all nodes always have a packet to send and are within carrier sense range of each other. Networks with a high density of clients and AP(s) are shown, via simulation, to achieve large throughput gains (up to 400% for 25 clients and AP(s)), over standard 802.11.