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High-Confidence Computing (HCC)

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Factor de Impacto:
9.0
Editor:
Elsevier
ISSN:
2667-2952
Vistas:
1297
Seguidores:
0

Solicitud de Artículos

High-Confidence Computing (HCC) is an academic journal published by Elsevier. (ISSN 2667-2952, impact factor 9.0, CCF C).

Aims & Scope An official Journal of the Shandong University The High-Confidence Computing Journal is dedicated to publish articles covering fundamental research outcomes that fusion the three domains of secure computing, precise computing, and intelligent computing, as well as complex system designs that jointly consider the properties of secure and trusted hardware/software, precise and process-traceable algorithms, and self-evolving systems that can adapt to new environments and support new applications. The journal intends to provide a unique interdisciplinary platform for researchers and practitioners who are interested in the basic research of high-confidence computing and the complex system developments considering high-confidence properties to demonstrate their novel and creative designs. Other than the original research papers on all aspects of high-confidence computing from theory and applications, the journal also publishes review articles with inspiring open research discussions that can motivate new ideas of realizing high-confidence computing. The journal accepts original research and review articles that address the challenges in all aspects of high-confidence computing, from theory to systems. Its contents are centered in the following three tracks: high-confidence computing theory and algorithms, architectures and platforms, software and systems. The Journal considers Original Article, Review, Case Report and Commentary. Specific topics include but are not limited to: • Expandable and accountable computing architectures • SDN-enabled and blockchain-enhanced computing architectures • NFV for dynamic function expansion and adaptation • Access control to secure open computing environments • TEE-enabled trusted data collection and hardware control • Cryptographic high-confidence primitives and applications • High-confidence system security and privacy • Malicious, damaged and white-noise data cleaning and extraction • Spatial-temporal big data fusion for intelligent decision making • Migration learning and digital-twin technologies • Cascading failure detection and recovery • Cascading vulnerability detection and positioning • Active defence technologies • Blockchain technologies and applications • High-confidence IoT • Machine learning security
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