Secure Motion Verification using the Doppler Effect

Schäfer, Matthias; Leu, P.; Lenders, Vincent; Schmitt, Jens

doi:10.1145/2939918.2939920

Cited by 29 publications

(16 citation statements)

References 24 publications

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“…It is a common phenomenon in wireless communications, which is widely used in many applications [51], [40]. However, some studies have suggested using the Doppler shift of an ADS-B signal to verify the velocity, and subsequently, the position of an aircraft [52], [53]. The Doppler shift effect is mainly used to verify whether the signal is coming from a source-in-motion, assuming that the attacker is likely to be in the static mode, while a real aircraft is constantly in motion when it flies.…”

Section: B Defense Using the Doppler Shiftmentioning

confidence: 99%

Cybersecurity Attacks on Software Logic and Error Handling Within ADS-B Implementations: Systematic Testing of Resilience and Countermeasures

Khandker¹,

Turtiainen²,

Costin³

et al. 2022

IEEE Trans. Aerosp. Electron. Syst.

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Automatic Dependent Surveillance-Broadcast (ADS-B) is a cornerstone of the next-generation digital sky and is now mandated in several countries. However, there have been many reports of serious security vulnerabilities in the ADS-B architecture. In this paper, we demonstrate and evaluate the impact of multiple cyberattacks on ADS-B via remote radio frequency links that affected various network, processing, and display subsystems used within the ADS-B ecosystem.Overall we implemented and tested 12 cyberattacks on ADS-B in a controlled environment, out of which 5 attacks were presented or implemented for the first time. For all these attacks, we developed a unique testbed that consisted of 13 hardware devices and 22 software that ran on Android, iOS, Linux, and Windows operating systems, which result in a total of 36 tested configurations. Each of the attacks was successful on various subsets of the tested configurations. In some attacks, we discovered wide qualitative variations and discrepancies in how particular configurations react to and treat ADS-B inputs that contain errors or contradicting flight information, with the main culprit almost always being the software implementation. In some other attacks, we managed to cause Denial of Service (DoS) by remotely crashing/impacting more than 50% of the test-set that corresponded to those attacks.Besides demonstrating successful attacks, we also implemented, investigated, and report herein some practical countermeasures to these attacks. We demonstrated that the strong relationship between the received signal strength and the distance-toemitter might help verify the aircraft's advertised ADS-B position and distance. For example, our best machine learning models achieved 90% accuracy in detecting spoofed ADS-B signals, which may be effectively used to distinguish ADS-B signals of real aircraft from spoofed signals of attackers.

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Section: B Defense Using the Doppler Shiftmentioning

confidence: 99%

Cybersecurity Attacks on Software Logic and Error Handling Within ADS-B Implementations: Systematic Testing of Resilience and Countermeasures

Khandker¹,

Turtiainen²,

Costin³

et al. 2022

IEEE Trans. Aerosp. Electron. Syst.

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“…Schäfer et al [109] discuss how the Doppler effect can be used to validate movement in an approach similar to those discussed above. Although their work primarily focuses on flying vehicles (e.g., airplanes), where distances are much greater and thus signal propagation takes much more time.…”

Section: B Data-centric Mechanismsmentioning

confidence: 99%

Survey on Misbehavior Detection in Cooperative Intelligent Transportation Systems

Heijden

Dietzel

Leinmüller

et al. 2019

IEEE Commun. Surv. Tutorials

181

146

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Cooperative Intelligent Transportation Systems (cITS) are a promising technology to enhance driving safety and efficiency. Vehicles communicate wirelessly with other vehicles and infrastructure, thereby creating a highly dynamic and heterogeneously managed ad-hoc network. It is these network properties that make it a challenging task to protect integrity of the data and guarantee its correctness. A major component is the problem that traditional security mechanisms like PKIbased asymmetric cryptography only exclude outsider attackers that do not possess key material. However, because attackers can be insiders within the network (i.e., possess valid key material), this approach cannot detect all possible attacks. In this survey, we present misbehavior detection mechanisms that can detect such insider attacks based on attacker behavior and information analysis. In contrast to well-known intrusion detection for classical IT systems, these misbehavior detection mechanisms analyze information semantics to detect attacks, which aligns better with highly application-tailored communication protocols foreseen for cITS. In our survey, we provide an extensive introduction to the cITS ecosystem and discuss shortcomings of PKI-based security. We derive and discuss a classification for misbehavior detection mechanisms, provide an in-depth overview of seminal papers on the topic, and highlight open issues and possible future research trends.

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“…Strohmeier et al [46], [49] survey the existing research on countermeasures. More specifically, Ghose and Lazos [10] as well as Schäfer et al [37], [38] and Liu et al [22] propose the usage of timing or Dopplershift characteristics to detect attacks on ADS-B. While this cannot protect from attacks, it still helps to identify malicious or inaccurate messages.…”

Section: Related Workmentioning

confidence: 99%

“…Since our system is solely based on an already existing infrastructure and does not require any modifications on aviation systems, it is non-invasive and could be implemented today easing very long certification processes. In contrast to existing solutions for air-traffic verification [10], [21], [22], [26], [37], [38], [52], [60], we do not require the measurement of time, frequency shifts, or any PHY layer features, but only use discrete sensor events.…”

Section: Introductionmentioning

confidence: 99%

Trust the Crowd: Wireless Witnessing to Detect Attacks on ADS-B-Based Air-Traffic Surveillance

Jansen

Niu

Xue

et al. 2021

Proceedings 2021 Network and Distributed System Security Symposium

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Automatic Dependent Surveillance-Broadcast (ADS-B) has been widely adopted as the de facto standard for air-traffic surveillance. Aviation regulations require all aircraft to actively broadcast status reports containing identity, position, and movement information. However, the lack of security measures exposes ADS-B to cyberattacks by technically capable adversaries with the purpose of interfering with air safety. In this paper, we develop a non-invasive trust evaluation system to detect attacks on ADS-B-based air-traffic surveillance using real-world flight data as collected by an infrastructure of ground-based sensors. Taking advantage of the redundancy of geographically distributed sensors in a crowdsourcing manner, we implement verification tests to pursue security by wireless witnessing. At the core of our proposal is the combination of verification checks and Machine Learning (ML)-aided classification of reception patterns-such that user-collected data cross-validates the data provided by other users. Our system is non-invasive in the sense that it neither requires modifications on the deployed hardware nor the software protocols and only utilizes already available data. We demonstrate that our system can successfully detect GPS spoofing, ADS-B spoofing, and even Sybil attacks for airspaces observed by at least three benign sensors. We are further able to distinguish the type of attack, identify affected sensors, and tune our system to dynamically adapt to changing air-traffic conditions.

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Secure Motion Verification using the Doppler Effect

Cited by 29 publications

References 24 publications

Cybersecurity Attacks on Software Logic and Error Handling Within ADS-B Implementations: Systematic Testing of Resilience and Countermeasures

Cybersecurity Attacks on Software Logic and Error Handling Within ADS-B Implementations: Systematic Testing of Resilience and Countermeasures

Survey on Misbehavior Detection in Cooperative Intelligent Transportation Systems

Trust the Crowd: Wireless Witnessing to Detect Attacks on ADS-B-Based Air-Traffic Surveillance

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