Topical Collection on 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020)

  in Special Issue   Posted on October 19, 2020

Information for the Special Issue

Submission Deadline: Mon 30 Nov 2020
Journal Impact Factor : 2.505
Journal Name : Neural Computing and Applications
Journal Publisher:
Website for the Special Issue: https://www.springer.com/journal/521/updates/18104738
Journal & Submission Website: https://www.springer.com/journal/521

Special Issue Call for Papers:

SPIoT 2020 is an international conference dedicated to promoting novel theoretical and applied research advances in the interdisciplinary agenda of Internet of things. The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020).

The “Internet of Things” heralds the connections of a nearly countless number of devices to the internet thus promising accessibility, boundless scalability, amplified productivity and a surplus of additional paybacks. The hype surrounding the IoT and its applications is already forcing companies to quickly upgrade their current processes, tools, and technology to accommodate massive data volumes and take advantage of insights. Since there is a vast amount of data generated by the IoT, a well-analysed data is extremely valuable. However, the large-scale deployment of IoT will bring new challenges and IoT security is one of them.

This special issue includes selected papers (with no less than 60% new content of the journal version) from The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), November 6 and 8, 2020 Shanghai, China as well as an open call (http://www.spiot2020.com/).

Topics of interests include, but are not limited to:

  • Novel machine learning and big data analytics methods for IoT security
  • Big data analytics/machine learning/deep learning for IoT security such as smart grid security analytics
  • Data mining and statistical modelling for the secure IoT
  • Machine learning and big data analytics architectures for IoT security
  • Machine learning based security detecting protocols
  • Machine learning experiments, test-beds and prototyping systems for IoT security
  • Analytics and machine learning applications to IoT security
  • Data based metrics and risk assessment approaches for IoT
  • Data confidentiality and privacy in IoT
  • Authentication and access control for data usage in IoT
  • Data-driven co-design of communication, computing and control for IoT security
  • Big data analytics/machine learning/deep learning edge/fog security
  • Emerging standards for IoT security

Guest Editors

Jinghua Zhao (Lead Guest Editor), University of Shanghai for Science and Technology, China, zhaojinghua@usst.edu.cnQingyuan Zhou, Changzhou Institute of Mechatronic Technology, China

Important Dates

Manuscript Due:            30th November 2020First Round of Reviews: 30th January 2020Final Decision:               31st March 2021

Peer Review Process

All the papers will go through a double blind review process and will be reviewed by at least two reviewers. A thorough check will be done and the guest editors will check any significant similarity between the manuscript under consideration and any published paper or submitted manuscripts of which they are aware. In such case, the article will be directly rejected without proceeding further. Guest editors will make all reasonable effort to receive the reviewer’s comments and recommendation on time.

The submitted papers must provide original research that has not been published nor currently under review by other venues. Conference papers should be clearly identified by the authors at the submission stage and an explanation should be provided about how such papers have been extended.  At least 60% of new content is expected.

Submission Guideline 

Submissions for the special issue should follow the submission format and guidelines of the journal at https://www.springer.com/journal/521/submission-guidelines.Each manuscript should not exceed 16 pages in length (inclusive of figures and tables).

Authors should select ‘SI: SPIoT-2020′ during the submission step ‘Additional Information’.

Manuscripts must be submitted to the journal online system at https://www.editorialmanager.com/ncaa/default.aspx. All papers will be refereed by experts in the field based on originality, significance, quality and clarity. Every submitted paper will be reviewed by at least two reviewers. The final acceptance is the Editor-in-Chief’s decision.

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