An Investigation of Byzantine Threats in Multi-Robot Systems

Deng, Gelei; Zhou, Yuan; Xu, Yuan; Zhang, Tianwei; Liu, Yang

doi:10.1145/3471621.3471867

Cited by 16 publications

(11 citation statements)

References 59 publications

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“…In a future in which robots, such as autonomous cars, collaborate on a large scale, security and data integrity will be one of the major concerns of consumers. In addition to the usual risks of infection and hijacking, byzantine data manipulation could lead to map merging poisoning and intentionally erroneous C-SLAM estimates (Deng et al, 2021). Thus further investigation and more efforts have to be deployed on system security.…”

Section: Resilient Inter-robot Communicationmentioning

confidence: 99%

Towards Collaborative Simultaneous Localization and Mapping: a Survey of the Current Research Landscape

Lajoie

Ramtoula

Wu³

et al. 2022

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Motivated by the tremendous progress, we witnessed in recent years, this paper presents a survey of the scientific literature on the topic of Collaborative Simultaneous Localization and Mapping (C-SLAM), also known as multi-robot SLAM. With fleets of self-driving cars on the horizon and the rise of multi-robot systems in industrial applications, we believe that Collaborative SLAM will soon become a cornerstone of future robotic applications. In this survey, we introduce the basic concepts of C-SLAM and present a thorough literature review. We also outline the major challenges and limitations of C-SLAM in terms of robustness, communication, and resource management. We conclude by exploring the area’s current trends and promising research avenues.

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Section: Resilient Inter-robot Communicationmentioning

confidence: 99%

Towards Collaborative Simultaneous Localization and Mapping: a Survey of the Current Research Landscape

Lajoie

Ramtoula

Wu³

et al. 2022

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show abstract

“…We do not consider sensor jamming attacks [92], [93] since they aim to crudely block the perceived data instead of covertly misleading RVs. Cyber attacks against RVs (e.g., software and ROS vulnerabilities [94], [95], in-vehicle networks [96]- [98], DNN backdoor [99], communication protocols [100], [101], side-channel leakage [102]) are excluded as well. Comparisons with existing surveys.…”

Section: Systematization Scopementioning

confidence: 99%

“…Figure 2 shows our action flow model, which consists of 12 interacted robot functions. This is established by surveying the function compositions and interactions of various RVs from both industrial ecosystems [131], [132] and academic papers [94], [100], [133]. Among them, sensors directly interact with five functions: Objection Detection (A1), Segmentation (A2), Localization/SLAM (A3), Speech Recognition (A4) and Distance Detection (A5).…”

Section: A Action Flow Modelmentioning

confidence: 99%

SoK: Rethinking Sensor Spoofing Attacks against Robotic Vehicles from a Systematic View

Xu¹,

Han²,

Deng³

et al. 2022

Preprint

Self Cite

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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 sensor spoofing vulnerabilities. With this model, we successfully discover 104 spoofing attack vectors, 25 of which have been verified by prior works, while 55 attacks are practical but never considered. (3) We design two novel attack methodologies to verify the feasibility of newly discovered spoofing attack vectors.

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“…SkyJack [ 13 ] is a drone hijacking software that can change the SSID of a drone and establish a malicious connection. This results in Byzantine faults in the MRS, which are difficult to identify [ 14 , 15 ]. Blockchain technology [ 16 ] has been highly successful in achieving Byzantine Fault Tolerance due to its consensus algorithm [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

IoT Security and Computation Management on a Multi-Robot System for Rescue Operations Based on a Cloud Framework

Roy

Hernandez

et al. 2022

Sensors

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There is a growing body of literature that recognizes the importance of Multi-Robot coordination and Modular Robotics. This work evaluates the secure coordination of an Unmanned Aerial Vehicle (UAV) via a drone simulation in Unity and an Unmanned Ground Vehicle (UGV) as a rover. Each robot is equipped with sensors to gather information to send to a cloud server where all computations are performed. Each vehicle is registered by blockchain ledger-based network security. In addition to these, relevant information and alerts are displayed on a website for the users. The usage of UAV–UGV cooperation allows for autonomous surveillance due to the high vantage field of view. Furthermore, the usage of cloud computation lowers the cost of microcontrollers by reducing their complexity. Lastly, blockchain technology mitigates the security issues related to adversarial or malicious robotic nodes connecting to the cluster and not agreeing to privacy rules and norms.

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An Investigation of Byzantine Threats in Multi-Robot Systems

Cited by 16 publications

References 59 publications

Towards Collaborative Simultaneous Localization and Mapping: a Survey of the Current Research Landscape

Towards Collaborative Simultaneous Localization and Mapping: a Survey of the Current Research Landscape

SoK: Rethinking Sensor Spoofing Attacks against Robotic Vehicles from a Systematic View

IoT Security and Computation Management on a Multi-Robot System for Rescue Operations Based on a Cloud Framework

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