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Security and privacy issues for artificial intelligence in edge-cloud computing

Journal of Cloud Computing welcomes submissions to the thematic series entitled "Security and privacy issues for artificial intelligence in edge-cloud computing"

Edge computing is emerging as a popular computing paradigm with the aim to minimize the delay between end-users and the cloud. A wide range of artificial intelligence applications benefit from the low latency offered by edge computing, e.g., driverless cars, smart homing, etc. However, edge computing suffers from capacity limitations and is challenged by computationally expensive artificial intelligent applications. To overcome these limitations, the edge-cloud computing paradigm offers a tradeoff between artificial intelligence applications’ requirements for computing resources and low latency.
Unlike the centralized cloud, in the edge-cloud environment, there is a lack of security technologies and privacy protection mechanisms specifically designed for artificial intelligence applications facilitated by the edge-cloud computing paradigm. In the edge-cloud environment, artificial intelligence applications are subject to a variety of security threats, such as data privacy disclosure, adversarial attacks, confidential attacks, etc.
This thematic series aims to solicit high-quality contributions that share and discuss recent advances and future trends of security and privacy issues for artificial intelligence in edge-cloud computing. The topics of interest include, but are not limited to:

  • AI-powered privacy protection in edge-cloud environment
  • Intelligent data preprocess, communications and integration for edge-cloud computing
  • Attacks vs.Countermeasures for intelligent applications in edge-cloud environment
  • Energy-efficient cloud-edge architecture with security guarantee
  • Intelligent application splitting for edge-cloud computing
  • Context-aware service offloading for edge-cloud computing
  • The design of AI-enabled hardware aspects in edge-cloud environment
  • The integration of distributed and decentralized signal processing via AI algorithms
  • Trust, reliability and dependability in edge-cloud computing
  • Industrial applications, data and platforms in edge-cloud computing

Guest editors

Lianyong Qi, Qufu Normal University, China
Jianxin Li, Beihang University, China
Nick Antonopoulos, Edinburgh Napier University, UK
Hao Wang, Norwegian University of Science and Technology, Norway

Submission due date: 1 September 2020

Submission instructionsBefore submitting your manuscript, please ensure you have carefully read the submission guidelines for Journal of Cloud Computing. The complete manuscript should be submitted through the Journal of Cloud Computing submission system. To ensure that you submit to the correct thematic series please select the appropriate thematic series in the drop-down menu upon submission. All submissions will undergo rigorous peer review and accepted articles will be published within the journal as a collection.

Submissions will also benefit from the usual advantages of open access publication: 

  • Rapid publication: Online submission, electronic peer review and production make the process of publishing your article simple and efficient 
  • High visibility and international readership in your field: Open access publication ensures high visibility and maximum exposure for your work - anyone with online access can read your article 
  • No space constraints: Publishing online means unlimited space for figures, extensive data and video footage
  • Authors retain copyright, licensing the article under a Creative Commons license: articles can be freely redistributed and reused as long as the article is correctly attributed.  

Annual Journal Metrics

  • 2022 Citation Impact
    4.0 - 2-year Impact Factor
    4.4 - 5-year Impact Factor
    1.711 - SNIP (Source Normalized Impact per Paper)
    0.976 - SJR (SCImago Journal Rank)

    2023 Speed
    10 days submission to first editorial decision for all manuscripts (Median)
    116 days submission to accept (Median)

    2023 Usage 
    49 Altmetric mentions 

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