Cybersecurity of Robotics and Autonomous Systems: Privacy and Safety

Lera, Francisco Javier Rodríguez; Llamas, Camino Fernández; Guerrero, Ángel Manuel; Olivera, Vicente Matellán

doi:10.5772/intechopen.69796

Cited by 30 publications

(18 citation statements)

References 12 publications

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“…One fact about ROS is that it was designed without taking into account security protections, because it was mainly designed for research purposes. In fact, as reported in [ 5 , 11 , 12 , 13 , 14 , 15 ], several security flaws were found in ROS. Additionally, malicious malware can easily interfere with ROS communications, read ongoing messages or supersede ROS nodes.…”

Section: Introductionmentioning

confidence: 70%

“…Therefore, the cyber-security threats and consequences on the robotic platforms must be extensively studied and investigated. However, it is currently well-known that cyber-security for the robotic platforms is considered a big challenge because it requires an inter-disciplinary effort [ 5 , 6 ]. As such, this subject is currently a major challenge for robotic and autonomous systems.…”

Section: Introductionmentioning

confidence: 99%

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Analyzing Cyber-Physical Threats on Robotic Platforms

Yousef

AlMajali

Ghalyon

et al. 2018

Sensors

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Robots are increasingly involved in our daily lives. Fundamental to robots are the communication link (or stream) and the applications that connect the robots to their clients or users. Such communication link and applications are usually supported through client/server network connection. This networking system is amenable of being attacked and vulnerable to the security threats. Ensuring security and privacy for robotic platforms is thus critical, as failures and attacks could have devastating consequences. In this paper, we examine several cyber-physical security threats that are unique to the robotic platforms; specifically the communication link and the applications. Threats target integrity, availability and confidential security requirements of the robotic platforms, which use MobileEyes/arnlServer client/server applications. A robot attack tool (RAT) was developed to perform specific security attacks. An impact-oriented approach was adopted to analyze the assessment results of the attacks. Tests and experiments of attacks were conducted in simulation environment and physically on the robot. The simulation environment was based on MobileSim; a software tool for simulating, debugging and experimenting on MobileRobots/ActivMedia platforms and their environments. The robot platform PeopleBotTM was used for physical experiments. The analysis and testing results show that certain attacks were successful at breaching the robot security. Integrity attacks modified commands and manipulated the robot behavior. Availability attacks were able to cause Denial-of-Service (DoS) and the robot was not responsive to MobileEyes commands. Integrity and availability attacks caused sensitive information on the robot to be hijacked. To mitigate security threats, we provide possible mitigation techniques and suggestions to raise awareness of threats on the robotic platforms, especially when the robots are involved in critical missions or applications.

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Section: Introductionmentioning

confidence: 70%

Section: Introductionmentioning

confidence: 99%

Analyzing Cyber-Physical Threats on Robotic Platforms

Yousef

AlMajali

Ghalyon

et al. 2018

Sensors

View full text Add to dashboard Cite

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“…However, "the more functions are performed across interconnected systems and devices, the more opportunities for weaknesses in those systems to arise, and the higher the risk of system failures or malicious attacks" (Michels and Walden, 2018). To date, nonetheless, there is little understanding to what extent an attacker can exploit the computational parts of a robot to affect the physical environment in industrial (Quarta et al, 2017), social (Lera et al, 2017), or medical environments (Bonaci et al, 2015), and what that would entail for the users involved in the interaction (Fosch- Villaronga and Mahler, 2021). Ethical issues of transparency and cybersecurity present also an important concern, and are yet not comprehensively addressed for robots and other cyber-physical systems, despite existing cases concerning the hacking of autonomous vehicles and healthcare devices such as pacemakers (Miller, 2019).…”

Section: Cyber Dimensionmentioning

confidence: 99%

Redefining Safety in Light of Human-Robot Interaction: A Critical Review of Current Standards and Regulations

et al. 2021

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Policymakers need to consider the impacts that robots and artificial intelligence (AI) technologies have on humans beyond physical safety. Traditionally, the definition of safety has been interpreted to exclusively apply to risks that have a physical impact on persons’ safety, such as, among others, mechanical or chemical risks. However, the current understanding is that the integration of AI in cyber-physical systems such as robots, thus increasing interconnectivity with several devices and cloud services, and influencing the growing human-robot interaction challenges how safety is currently conceptualised rather narrowly. Thus, to address safety comprehensively, AI demands a broader understanding of safety, extending beyond physical interaction, but covering aspects such as cybersecurity, and mental health. Moreover, the expanding use of machine learning techniques will more frequently demand evolving safety mechanisms to safeguard the substantial modifications taking place over time as robots embed more AI features. In this sense, our contribution brings forward the different dimensions of the concept of safety, including interaction (physical and social), psychosocial, cybersecurity, temporal, and societal. These dimensions aim to help policy and standard makers redefine the concept of safety in light of robots and AI’s increasing capabilities, including human-robot interactions, cybersecurity, and machine learning.

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“…The perception module combines data from various sensors to create a picture of the environment through a sophisticated algorithm. As discussed in [21], there are two types of sensors: Exteroceptive and Proprioceptive sensors. Exteroceptive sensors are those that give information about robot workspaces like LASERs, LiDAR, and cameras.…”

Section: Autonomous System (As) Architecturementioning

confidence: 99%

A Non-Cooperative Game based Model for the Cybersecurity of Autonomous Systems

Jahan

Sun

Niyaz

2020

2020 IEEE Security and Privacy Workshops (SPW)

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Autonomous systems (AS) would soon revolutionize the way we live and work. The days are not so far when these systems, from delivery drones to driverless cars, would be seen around us. These systems are connected and rely heavily on the communication network for the information exchange, hence prone to several attacks. Human lives will be at risk if these systems are compromised. Cybersecurity modeling and attack analysis of AS needs the utmost attention of the research community. Primarily, a typical AS has three modules -perception, cognition, and control -and each one of them comes with their own vulnerabilities. In this work, we propose a new AS architecture that may prove useful in AS cybersecurity modeling. We also model the attacks on them, and defense mechanisms applied to these modules using a non-cooperative non-zero sum game. Finally, we solve this game to obtain optimal strategies to maintain a secure system state.

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Cybersecurity of Robotics and Autonomous Systems: Privacy and Safety

Cited by 30 publications

References 12 publications

Analyzing Cyber-Physical Threats on Robotic Platforms

Analyzing Cyber-Physical Threats on Robotic Platforms

Redefining Safety in Light of Human-Robot Interaction: A Critical Review of Current Standards and Regulations

A Non-Cooperative Game based Model for the Cybersecurity of Autonomous Systems

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