Investigation of multi-device location spoofing attacks on air traffic control and possible countermeasures

Moser, Daniel; Leu, P.; Lenders, Vincent; Ranganathan, Aanjhan; Ricciato, Fabio; Čapkun, Srđjan

doi:10.1145/2973750.2973763

Cited by 38 publications

(25 citation statements)

References 26 publications

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“…In our particular application, the classification of the aircraft will be used to understand if the received signals are really generated from the expected aircraft or not; many methods are proposed in literature to solve this kind of problem [10,21]; each method has pros and cons with different performances for different applications.…”

Section: Aircraft Classification Methodsmentioning

confidence: 99%

Air Traffic Security: Aircraft Classification Using ADS-B Message’s Phase-Pattern

2017

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Automatic Dependent Surveillance-Broadcast (ADS-B) is a surveillance system used in Air Traffic Control. With this system, the aircraft transmits their own information (identity, position, velocity, etc.) to any equipped listener for surveillance scope. The ADS-B is based on a very simple protocol and does not provide any kind of authentication and encryption, making it vulnerable to many types of cyber-attacks. In the paper, the use of the airplane/transmitter carrier phase is proposed as a feature to perform a classification of the aircraft and, therefore, distinguish legitimate messages from fake ones. The feature extraction process is described and a classification method is selected. Finally, a complete intruder detection algorithm is proposed and evaluated with real data.

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Section: Aircraft Classification Methodsmentioning

confidence: 99%

Air Traffic Security: Aircraft Classification Using ADS-B Message’s Phase-Pattern

2017

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“…There are various approaches of physical layer based technology, such as approaches based on received signal strength (RSS, [27,28]), based on frequency offset caused by imperfections in the transmitters synchronization [11], or based on the carrier phase (e.g., [29]). While these methods can effectively defeat jamming and modification attacks, the inherently lower performance makes them difficult to use in a large-scale system such as ADS-B.…”

Section: Secure Broadcast Authentication Technologymentioning

confidence: 99%

“…Moser et al [11] first proposed the multidevice false data injection attack of ADS-B multilateration system in ATC surveillance. However, Moser et al simulate the arrival time of the real transmitter without utilizing the characteristics of the multilateration algorithm.…”

Section: Introductionmentioning

confidence: 99%

Multidevice False Data Injection Attack Models of ADS-B Multilateration Systems

Shang

Wang

Yan

et al. 2019

Security and Communication Networks

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Location verification is a promising approach among various ADS-B security mechanisms, which can monitor announced positions in ADS-B messages with estimated positions. Based on common assumption that the attacker is equipped with only a single device, this mechanism can estimate the position state through analysis of time measurements of messages using multilateration algorithm. In this paper, we propose the formal model of multidevice false data injection attacks in the ATC system against the location verification. Assuming that attackers equipped with multiple devices can manipulate the ADS-B messages in distributed receivers without any mutual interference, such attacker can efficiently construct attack vectors to change the results of multilateration. The feasibility of a multidevice false data injection attack is demonstrated experimentally. Compared with previous multidevice attacks, the multidevice false data injection attacks can offer lower cost and more covert attacks. The simulation results show that the proposed attack can reduce the attackers’ cost by half and achieve better time synchronization to bypass the existing anomaly detection. Finally, we discuss the real-world constraints that limit their effectiveness and the countermeasures of these attacks.

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“…the OpenSky Network [20], Flightaware [5], Flightradar24 [6] and many others. These sensor networks can leverage the time-of-arrival (TOA) of Mode S signals for various kinds of applications, including aircraft localization [20,22], air traffic data verification [13,16,17,19,21], and self-localization [15]. In those applications, a set of cooperating receivers measure locally the TOA of the arriving signals and then send these data to a central computation server.…”

Section: Introductionmentioning

confidence: 99%

Nanosecond-Precision Time-of-Arrival Estimation for Aircraft Signals with Low-Cost SDR Receivers

Calvo-Palomino

Ricciato

Repas

et al. 2018

2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)

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Precise Time-of-Arrival (TOA) estimations of aircraft and drone signals are important for a wide set of applications including aircraft/drone tracking, air traffic data verification, or self-localization. Our focus in this work is on TOA estimation methods that can run on low-cost software-defined radio (SDR) receivers, as widely deployed in Mode S / ADS-B crowdsourced sensor networks such as the OpenSky Network. We evaluate experimentally classical TOA estimation methods which are based on a cross-correlation with a reconstructed message template and find that these methods are not optimal for such signals. We propose two alternative methods that provide superior results for real-world Mode S / ADS-B signals captured with low-cost SDR receivers. The best method achieves a standard deviation error of 1.5 ns.

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Investigation of multi-device location spoofing attacks on air traffic control and possible countermeasures

Cited by 38 publications

References 26 publications

Air Traffic Security: Aircraft Classification Using ADS-B Message’s Phase-Pattern

Air Traffic Security: Aircraft Classification Using ADS-B Message’s Phase-Pattern

Multidevice False Data Injection Attack Models of ADS-B Multilateration Systems

Nanosecond-Precision Time-of-Arrival Estimation for Aircraft Signals with Low-Cost SDR Receivers

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