2022/05/10 by Xu Yuan, Xingshuo Han, Xu, Yuan +9 · 7 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · #Artificial intelligence #Bacillus and Francisella bacterial research #Computer science #Computer security #Cryptographic Implementations and Security #Forensic and Genetic Research #Function (biology) #IP address spoofing #Key (lock) #Property (philosophy) #Spoofing attack #The Internet #World Wide Web
paper · pdf · doi:10.48550/arxiv.2205.04662
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2022/05/10 · openalex created_date 2023/02/13 · openalex updated_date 2026/07/28
Robotic Vehicles (RVs) have gained great popularity over the past few years. Meanwhile, they are also demonstrated to be vulnerable to sensor spoofing attacks. Although a wealth of research works have presented various attacks, some key questions remain unanswered: are these existing works complete enough to cover all the sensor spoofing threats? If not, how many attacks are not explored, and how difficult is it to realize them? This paper answers the above questions by comprehensively systematizing the knowledge of sensor spoofing attacks against RVs. Our contributions are threefold. (1) We identify seven common attack paths in an RV system pipeline. We categorize and assess existing spoofing attacks from the perspectives of spoofer property, operation, victim characteristic and attack goal. Based on this systematization, we identify 4 interesting insights about spoofing attack designs. (2) We propose a novel action flow model to systematically describe robotic function executions and unexplored sensor spoofing threats. With this model, we successfully discover 103 spoofing attack vectors, 26 of which have been verified by prior works, while 77 attacks are never considered. (3) We design two novel attack methodologies to verify the feasibility of newly discovered spoofing attack vectors.