Detecting Attacks Against Robotic Vehicles

Choi, Hyung Do; Lee, Wen‐Chuan; Aafer, Yousra; Fei, Fan; Tu, Zhan; Zhang, Xiangyu; Xu, Dongyan

doi:10.1145/3243734.3243752

Cited by 141 publications

(69 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Record D, and the following trajectory as track [1]; 8: end if 9: end while 10: Reset: R a moves to a posture p a such that R a is in R v 's +90 • direction with distance = D, i.e., α 1 = θ + 90 • ; 11: while ∆θ = 0 do 12:…”

Section: B Intentional-learning: Trajectory Trialmentioning

confidence: 99%

“…Due to the increasing usage of mobile robots in a wide range of application domains, the security issue has become an essential requirement and imperative challenge [1]. The security shows the ability of a system to govern malicious behaviors or unanticipated events [2].…”

Section: Introductionmentioning

confidence: 99%

“…Even the important values stored in memory (e.g, EEPROM, Flash memory) can be corrupted by heating up a memory cell while the device is without ang damage [15]. Compared with cyber attacks, these physical attacks are straightforward to implement, and traditional detection techniques from computer security community are usually not effective and powerful to handle them [1]. Nevertheless, this does not mean these physical attacks are impeccable.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Learning-based Intelligent Attack against Formation Control with Obstacle-avoidance

Chen

et al. 2019

2019 American Control Conference (ACC)

View full text Add to dashboard Cite

The security issue of mobile robots have attracted considerable attention in recent years. Most existing works focus on detection and countermeasures for some classic attacks from cyberspace. Nevertheless, those work are generally based on some prior assumptions for the attacker (e.g., the system dynamics is known, or internal access is compromised). A few work are delicated to physical attacks, however, there still lacks certain intelligence and advanced control design. In this paper, we propose a physical-based and intelligent attack framework against the obstacle-avoidance of mobile robots. The novelty of our work lies in the following: i) Without any prior information of the system dynamics, the attacker can learn the detection area and goal position of a mobile robot by trial and observation, and the obstacle-avoidance mechanism is learned by support vector regression (SVR) method; ii) Considering different attack requirements, different attack strategies are proposed to implement the attack efficiently; iii) The framework is suitable for holonomic and non-holonomic mobile robots, and the algorithm performance analysis about time complexity and optimality is provided. Furthermore, the condition is obtained to guarantee the success of the attack. Simulations illustrate the effectiveness of the proposed framework.The authors are with the

show abstract

Section: B Intentional-learning: Trajectory Trialmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Learning-based Intelligent Attack against Formation Control with Obstacle-avoidance

Chen

et al. 2019

2019 American Control Conference (ACC)

View full text Add to dashboard Cite

show abstract

“…Attacks also target robotic vehicles like drones and ground rovers. 7 Choi et al consider robotic vehicles as a type of cyber-physical systems that consist of both cyber and physical components working jointly to support the vehicle's operations in the physical world. The authors enumerate many cases (eg, GPS spoofing and ABS tampering) that show how vulnerable robotic vehicles are to attacks and suggest an invariant approach to address some vulnerabilities.…”

Section: Security Of Iot In Briefmentioning

confidence: 99%

“…Similar news is reported in the automotive industry when a Jeep Cherokee was hijacked turning off the transmission while the vehicle was on the freeway. Attacks also target robotic vehicles like drones and ground rovers . Choi et al consider robotic vehicles as a type of cyber‐physical systems that consist of both cyber and physical components working jointly to support the vehicle's operations in the physical world.…”

Section: Introductionmentioning

confidence: 99%

Open challenges in vetting the internet‐of‐things

Maamar

Kajan

Asim

et al. 2019

Internet Technology Letters

View full text Add to dashboard Cite

Internet‐of‐Thing (IoT) is a rapid‐emerging technology that exploits the concept of internetwork to connect things such as physical devices and objects together. A huge number of things (6.4 billion are in use in 2016) are already acting without direct human control raising a lot of concerns about the readiness and appropriateness of existing security practices, techniques, and tools to secure the data collected and protect people's private lives. As a first step, this paper presses the importance of having a dedicated process for vetting IoT (by analogy to vetting mobile apps) with focus on exposing things' vulnerabilities that could be the primary source of attacks. These vulnerabilities are identified according to things' duties decomposed into sensing, actuating, and communicating. A set of questions shed light on things' vulnerabilities per type of duty.

show abstract