10 research outputs found
Signal Identification and Entrainment for Practical FMCW Radar Spoofing Attacks
This paper proposes a method of passively estimating the parameters of
frequency-modulated-continuous-wave (FMCW) radar signals with a wide range of
structural parameter values and analyzes how a malicious actor could employ
such estimates to track and spoof a target radar. When radars are implemented
to support automated driver assistance systems, an intelligent spoofer has the
potential to substantially disrupt safe navigation by inducing its target to
perceive false objects. Such a spoofer must acquire highly accurate estimates
of the target radar's chirp sweep, timing, and frequency parameters while
additionally tracking and compensating for time and Doppler shifts due to clock
errors and relative movement. This is a difficult task for millimeter-wave
radars due to severe Doppler shifts and fast sweep rates, especially when the
spoofer uses off-the-shelf FMCW equipment. Algorithms and techniques for
acquiring and tracking an FMCW radar are proposed and verified through
simulation, which will help guide future decisions on appropriate radar
spoofing countermeasures
MadRadar: A Black-Box Physical Layer Attack Framework on mmWave Automotive FMCW Radars
Frequency modulated continuous wave (FMCW) millimeter-wave (mmWave) radars
play a critical role in many of the advanced driver assistance systems (ADAS)
featured on today's vehicles. While previous works have demonstrated (only)
successful false-positive spoofing attacks against these sensors, all but one
assumed that an attacker had the runtime knowledge of the victim radar's
configuration. In this work, we introduce MadRadar, a general black-box radar
attack framework for automotive mmWave FMCW radars capable of estimating the
victim radar's configuration in real-time, and then executing an attack based
on the estimates. We evaluate the impact of such attacks maliciously
manipulating a victim radar's point cloud, and show the novel ability to
effectively `add' (i.e., false positive attacks), `remove' (i.e., false
negative attacks), or `move' (i.e., translation attacks) object detections from
a victim vehicle's scene. Finally, we experimentally demonstrate the
feasibility of our attacks on real-world case studies performed using a
real-time physical prototype on a software-defined radio platform
How Physicality Enables Trust: A New Era of Trust-Centered Cyberphysical Systems
Multi-agent cyberphysical systems enable new capabilities in efficiency,
resilience, and security. The unique characteristics of these systems prompt a
reevaluation of their security concepts, including their vulnerabilities, and
mechanisms to mitigate these vulnerabilities. This survey paper examines how
advancement in wireless networking, coupled with the sensing and computing in
cyberphysical systems, can foster novel security capabilities. This study
delves into three main themes related to securing multi-agent cyberphysical
systems. First, we discuss the threats that are particularly relevant to
multi-agent cyberphysical systems given the potential lack of trust between
agents. Second, we present prospects for sensing, contextual awareness, and
authentication, enabling the inference and measurement of ``inter-agent trust"
for these systems. Third, we elaborate on the application of quantifiable trust
notions to enable ``resilient coordination," where ``resilient" signifies
sustained functionality amid attacks on multiagent cyberphysical systems. We
refer to the capability of cyberphysical systems to self-organize, and
coordinate to achieve a task as autonomy. This survey unveils the cyberphysical
character of future interconnected systems as a pivotal catalyst for realizing
robust, trust-centered autonomy in tomorrow's world
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Towards secure & robust PNT for automated systems
This dissertation makes four contributions in support of secure and robust position, navigation, and timing (PNT) for automated systems. The first two relate to PNT security while the latter two address robust positioning for automated ground vehicles.
The first contribution is a fundamental theory for provably-secure clock synchronization between two agents in a distributed automated system. All one-way synchronization protocols, such as those based on the Global Positioning System (GPS) and other Global Navigation Satellite Systems (GNSS), are shown to be vulnerable to man-in-the-middle delay attacks. This contribution is the first to identify the necessary and sufficient conditions for provably secure clock synchronization.
The second contribution, also related to PNT security, is a three-year study of the world-wide GPS interference landscape based on data from a dual-frequency GNSS receiver operating continuously on the International Space Station (ISS). This work is the first publicly-reported space-based survey of GNSS interference, and unveils previously-unreported GNSS interference activity.
The third contribution is a novel ground vehicle positioning technique that is robust to GNSS signal blockage, poor lighting conditions, and adverse weather events such as heavy rain and dense fog. The technique relies on sensors that are commonly available on automated vehicles and are insensitive to lighting and inclement weather: automotive radar, low-cost inertial measurement units (IMUs), and GNSS. Remarkably, it is shown that, given a prior radar map, the proposed technique operating on data from off-the-shelf all-weather automotive sensors can maintain sub-50-cm horizontal position accuracy during 60 min of GNSS-denied driving in downtown Austin, TX.
This dissertation’s final contribution is an analysis and demonstration of the feasibility of crowd-sourced digital mapping for automated vehicles. Localization techniques, such as the one described in the previous contribution, rely on such digital maps for accuracy and robustness. A key enabler for large-scale up-to-date maps is enlisting the help of the very consumer vehicles that need the map to build and update it. A method for fusing multi-session vision data into a unified digital map is developed. The asymptotic limit of such a map’s globally-referenced position accuracy is explored for the case in which the mapping agents rely on low-cost GNSS receivers performing standard code-phase-based navigation. Experimental validation along a semi-urban route shows that low-cost consumer vehicles incrementally tighten the accuracy of the jointly-optimized digital map over time enough to support sub-lane-level positioning in a global frame of reference.Electrical and Computer Engineerin
Unmanned Aircraft Systems in the Cyber Domain
Unmanned Aircraft Systems are an integral part of the US national critical infrastructure. The authors have endeavored to bring a breadth and quality of information to the reader that is unparalleled in the unclassified sphere. This textbook will fully immerse and engage the reader / student in the cyber-security considerations of this rapidly emerging technology that we know as unmanned aircraft systems (UAS). The first edition topics covered National Airspace (NAS) policy issues, information security (INFOSEC), UAS vulnerabilities in key systems (Sense and Avoid / SCADA), navigation and collision avoidance systems, stealth design, intelligence, surveillance and reconnaissance (ISR) platforms; weapons systems security; electronic warfare considerations; data-links, jamming, operational vulnerabilities and still-emerging political scenarios that affect US military / commercial decisions.
This second edition discusses state-of-the-art technology issues facing US UAS designers. It focuses on counter unmanned aircraft systems (C-UAS) – especially research designed to mitigate and terminate threats by SWARMS. Topics include high-altitude platforms (HAPS) for wireless communications; C-UAS and large scale threats; acoustic countermeasures against SWARMS and building an Identify Friend or Foe (IFF) acoustic library; updates to the legal / regulatory landscape; UAS proliferation along the Chinese New Silk Road Sea / Land routes; and ethics in this new age of autonomous systems and artificial intelligence (AI).https://newprairiepress.org/ebooks/1027/thumbnail.jp