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Editorial: Special Issue on Cyber-Physical Security and Zero Trust

Published: 10 January 2024 Publication History
In the rapidly evolving realm of cyber-physical systems and sensor network systems, the convergence of security imperatives with the zero-trust stands paradigm as a focal point. This special issue presents a curated selection of papers that delve into the intricate balance between innovation and resilience within this dynamic landscape.
Adaptability in Real-Time:
The initial cluster of papers delves into real-time cyber-physical security solutions, highlighting the pivotal role of integrated learning approaches. These contributions underscore the necessity for agility in countering the persistent evolution of threats.
Guardians of Privacy and Trust: Blockchain, Beyond, and Zero-Trust Consensus:
The second cluster illuminates innovative approaches to secure data sharing, privacy protection, and consensus algorithms for blockchain security. Leveraging multi-sharding blockchain, these papers redefine trust architectures, playing a crucial role in fortifying the foundations of cyber-physical security.
Vigilance in Limited Locales: Detection and Defense:
Moving beyond theoretical frameworks, the third cluster addresses challenges in cyber-physical attack detection under limited local information. Utilizing ensemble multi-node multi-class classification approaches, these papers exemplify a commitment to fortifying systems in resource-constrained environments.
Advancements in Security Frameworks:
Adding another layer of depth, our collection encompasses pioneering work in evolving security frameworks. This aspect explores novel methodologies and strategies, contributing to the ongoing discourse on fortifying cyber-physical systems.
As we embark on this intellectual journey, we invite readers to explore the forefront of cyber-physical security and zero trust. The amalgamation of these disciplines holds the promise of reshaping the foundation upon which we build the future of interconnected technologies, including sensor networks, CPS, IoT, and so on. Our sincere gratitude extends to the authors for their invaluable contributions, reviewers for their insightful assessments, and the editorial team for their unwavering dedication in bringing this special issue to fruition.
Fangyu Li
Beijing University of Technology, China
WenZhan Song
University of Georgia, USA
Xiaohua Xu
University of Science and Technology of China, China
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  • (2024)Simple but Effective Raw-Data Level Multimodal Fusion for Composed Image RetrievalProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657727(229-239)Online publication date: 10-Jul-2024

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        Published In

        cover image ACM Transactions on Sensor Networks
        ACM Transactions on Sensor Networks  Volume 20, Issue 2
        March 2024
        572 pages
        EISSN:1550-4867
        DOI:10.1145/3618080
        • Editor:
        • Wen Hu
        Issue’s Table of Contents

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        Association for Computing Machinery

        New York, NY, United States

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        Publication History

        Published: 10 January 2024
        Published in TOSN Volume 20, Issue 2

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        • (2024)Simple but Effective Raw-Data Level Multimodal Fusion for Composed Image RetrievalProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657727(229-239)Online publication date: 10-Jul-2024

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