Cited By
View all- Zhong KYang ZYu SLi K(2024)Deep Reinforcement Learning-based Multi-Layer Cascaded Resilient Recovery for Cyber-Physical SystemsIEEE Transactions on Services Computing10.1109/TSC.2024.3478729(1-14)Online publication date: 2024
CPSIoTSec '22: 4th Workshop on CPS & IoT Security and Privacy
Pages 3533 - 3534
Abstract
There is a rapidly growing interest in the security of cyber-physical systems (CPS) and internet-of-things (IoT) in industry, government and academia. This interest is also reflected in this workshop that from 2019 has been part of the ACM Conference on Computer and Communications Security, which originally hosted two workshops: One on CPS security and privacy (running 5 times in the past) and one on IoT security and privacy (running 2 times in the past). Due to the close connection of the two topics, the Steering Committees of the two workshops decided in 2020 to merge towards delivering a world-class event on CPS&IoT security and privacy. CPSIoTSec'22 corresponds to the fourth edition of this merger.
CPS&IoTSec'22 attracted 16 submissions, which were assigned to four independent reviewers. Following a rigorous peer-review process, 3 full papers and 4 short papers were accepted, achieving an acceptance rate of 43.75%. We would like to express our deepest thanks to the CPS&IoTSec'22 Steering Committee for entrusting us with organizing the workshop, and all the members of the program committee for their valuable reviews and discussions. Likewise, we would like to thank all the authors who submitted their contributions in the CPS & IoT Security field. The complete CPSIoTSec'22 workshop proceedings are available at: https://dl.acm.org/doi/proceedings/10.1145/3560826
Index Terms
- CPSIoTSec '22: 4th Workshop on CPS & IoT Security and Privacy
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Information & Contributors
Information
Published In
November 2022
3598 pages
ISBN:9781450394505
DOI:10.1145/3548606
- General Chairs:
- Heng Yin,
- Angelos Stavrou,
- Program Chairs:
- Cas Cremers,
- Elaine Shi
Copyright © 2022 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 07 November 2022
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Conference
CCS '22
Sponsor:
CCS '22: 2022 ACM SIGSAC Conference on Computer and Communications Security
November 7 - 11, 2022
CA, Los Angeles, USA
Acceptance Rates
Overall Acceptance Rate 1,261 of 6,999 submissions, 18%
Upcoming Conference
CCS '25
- Sponsor:
- sigsac
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Cited By
View all- Zhong KYang ZYu SLi K(2024)Deep Reinforcement Learning-based Multi-Layer Cascaded Resilient Recovery for Cyber-Physical SystemsIEEE Transactions on Services Computing10.1109/TSC.2024.3478729(1-14)Online publication date: 2024
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