Tobias Lüscher (ETH Zurich), Martin Strohmeier (Cyber-Defence Campus, armasuisse S+T), Vincent Lenders (Cyber-Defence Campus, armasuisse S+T)

Automatic Dependent Surveillance - Contract (ADS-C) is an satellite-based aviation datalink application used to monitor aircraft in remote regions. It is a crucial method for air traffic control to track aircraft where other protocols such as ADS-B lack connectivity. Even though it has been conceived more than 30 years ago, and other legacy communication protocols in aviation have shown to be vulnerable, ADS-C’s security has not been investigated so far in the literature. We conduct a first investigation to close this gap. First, we compile a comprehensive overview of the history, impact, and technical details of ADSC and its lower layers. Second, we build two software-defined radio receivers in order to analyze over 120’000 real-world ADSC messages. We further illustrate ADS-C’s lack of authentication by implementing an ADS-C transmitter, which is capable of generating and sending arbitrary ADS-C messages. Finally, we use the channel control offered through a software-defined ADSC receiver and transmitter as a basis for an in-depth analysis of the protocol weaknesses of the ADS-C system. The found vulnerabilities range from passively tracking aircraft to actively altering the position of actual aircraft through attacks on the downlink and the uplink. We assess the difficulty and impact of these attacks and discuss potential countermeasures.

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Eavesdropping on Black-box Mobile Devices via Audio Amplifier's EMR

Huiling Chen (College of Computer Science and Electronic Engineering, Hunan University, Changsha, China), Wenqiang Jin (College of Computer Science and Electronic Engineering, Hunan University, Changsha, China), Yupeng Hu (College of Computer Science and Electronic Engineering, Hunan University, Changsha, China), Zhenyu Ning (College of Computer Science and Electronic Engineering, Hunan University, Changsha, China), Kenli Li (College…

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Maginot Line: Assessing a New Cross-app Threat to PII-as-Factor...

Fannv He (National Computer Network Intrusion Protection Center, University of Chinese Academy of Sciences, China), Yan Jia (DISSec, College of Cyber Science, Nankai University, China), Jiayu Zhao (National Computer Network Intrusion Protection Center, University of Chinese Academy of Sciences, China), Yue Fang (National Computer Network Intrusion Protection Center, University of Chinese Academy of Sciences, China),…

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EyeSeeIdentity: Exploring Natural Gaze Behaviour for Implicit User Identification...

L Yasmeen Abdrabou (Lancaster University), Mariam Hassib (Fortiss Research Institute of the Free State of Bavaria), Shuqin Hu (LMU Munich), Ken Pfeuffer (Aarhus University), Mohamed Khamis (University of Glasgow), Andreas Bulling (University of Stuttgart), Florian Alt (University of the Bundeswehr Munich)

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Stacking up the LLM Risks: Applied Machine Learning Security

Dr. Gary McGraw, Berryville Institute of Machine Learning

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