Seonghoon Jeong, Eunji Park, Kang Uk Seo, Jeong Do Yoo, and Huy Kang Kim (Korea University)

MAVLink protocol is a de facto standard protocol used to communicate between unmanned vehicle and ground control system (GCS). Given the nature of the system, unmanned vehicles use MAVLink to communicate with a GCS to be monitored and controlled. Such communication continues to grow on the Internet due to its rapidly grown nature. In the past few years, the unmanned vehicle security has been one of the key research topics in the security field. However, existing research has mainly focused on the sensor- and GPS-based attack detection methods. To this end, we propose MUVIDS, a network-level intrusion detection system to protect MAVLink-enabled unmanned vehicles managed by GCS over the Internet. MUVIDS includes two Long short-term memory models that leverage a sequential MAVLink stream from a victim vehicle. The two models are designed to solve a binary classification problem (in case of labels are available) and a next MAVLink message prediction problem (in case of no label is available), respectively. The experiment was performed on a software-in-the-loop unmanned aerial vehicle (UAV) simulator and a hardware-in-the-loop UAV simulator. The experiment result confirms that MUVIDS detects false MAVLink injection attacks effectively.

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Physical Layer Data Manipulation Attacks on the CAN Bus

Abdullah Zubair Mohammed (Virginia Tech), Yanmao Man (University of Arizona), Ryan Gerdes (Virginia Tech), Ming Li (University of Arizona) and Z. Berkay Celik (Purdue University)

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PASS: A System-Driven Evaluation Platform for Autonomous Driving Safety...

Zhisheng Hu (Baidu Security), Junjie Shen (UC Irvine), Shengjian Guo (Baidu Security), Xinyang Zhang (Baidu Security), Zhenyu Zhong (Baidu Security), Qi Alfred Chen (UC Irvine) and Kang Li (Baidu Security)

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Demo #15: Remote Adversarial Attack on Automated Lane Centering

Yulong Cao (University of Michigan), Yanan Guo (University of Pittsburgh), Takami Sato (UC Irvine), Qi Alfred Chen (UC Irvine), Z. Morley Mao (University of Michigan) and Yueqiang Cheng (NIO)

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Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)