Invited: Waving the Double-Edged Sword: Building Resilient CAVs with Edge and Cloud Computing

The rapid advancement of edge and cloud computing platforms, vehicular ad-hoc networks, and machine learning techniques have brought both opportunities and challenges for next-generation connected and automated vehicles (CAVs). On the one hand, these technologies can enable vehicles to leverage more...

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Vydáno v:2023 60th ACM/IEEE Design Automation Conference (DAC) s. 1 - 4
Hlavní autoři: Liu, Xiangguo, Luo, Yunpeng, Goeckner, Anthony, Chakraborty, Trishna, Jiao, Ruochen, Wang, Ningfei, Wang, Yixuan, Sato, Takami, Chen, Qi Alfred, Zhu, Qi
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 09.07.2023
Témata:
Ad hoc networks
Cloud computing
connected and autonomous vehicles
edge computing
Safety
Security
Servers
Uncertainty
V2X
Wireless communication
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Abstract The rapid advancement of edge and cloud computing platforms, vehicular ad-hoc networks, and machine learning techniques have brought both opportunities and challenges for next-generation connected and automated vehicles (CAVs). On the one hand, these technologies can enable vehicles to leverage more computing power from edge and cloud servers and to share information with each other and surrounding infrastructures for better situation awareness and more intelligent decision making. On the other hand, the more distributed computing process and the wireless nature of V2X (vehicle-to-everything) communication expose vulnerabilities to various disturbances and attacks. In this paper, we discuss the security and safety challenges for edge- and cloud-enabled CAVs, particularly when they are under environment interferences, execution errors, and malicious attacks, and we will introduce our recent work and future directions in developing system-driven, end-to-end methodologies and tools to address these challenges and ensure system resiliency under uncertainties.
AbstractList The rapid advancement of edge and cloud computing platforms, vehicular ad-hoc networks, and machine learning techniques have brought both opportunities and challenges for next-generation connected and automated vehicles (CAVs). On the one hand, these technologies can enable vehicles to leverage more computing power from edge and cloud servers and to share information with each other and surrounding infrastructures for better situation awareness and more intelligent decision making. On the other hand, the more distributed computing process and the wireless nature of V2X (vehicle-to-everything) communication expose vulnerabilities to various disturbances and attacks. In this paper, we discuss the security and safety challenges for edge- and cloud-enabled CAVs, particularly when they are under environment interferences, execution errors, and malicious attacks, and we will introduce our recent work and future directions in developing system-driven, end-to-end methodologies and tools to address these challenges and ensure system resiliency under uncertainties.
Author Goeckner, Anthony
Luo, Yunpeng
Sato, Takami
Liu, Xiangguo
Chakraborty, Trishna
Wang, Yixuan
Jiao, Ruochen
Wang, Ningfei
Chen, Qi Alfred
Zhu, Qi
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  givenname: Takami
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  givenname: Qi Alfred
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  givenname: Qi
  surname: Zhu
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  email: qzhu@northwestern.edu
  organization: Northwestern University,Department of Electrical and Computer Engineering,USA
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SubjectTerms Ad hoc networks
Cloud computing
connected and autonomous vehicles
edge computing
Safety
Security
Servers
Uncertainty
V2X
Wireless communication
Title Invited: Waving the Double-Edged Sword: Building Resilient CAVs with Edge and Cloud Computing
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