Skip to main content
SpringerLink
Log in
Springer
Neural Computing and Applications
Publishing model:
Hybrid

Neural Computing and Applications - Topical Collection on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIOT 2023)

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. The philosophy behind machine learning is to automate the creation of analytical models in order to enable algorithms to learn continuously with the help of available data. Continuously evolving models produce increasingly positive results, reducing the need for human interaction. These evolved models can be used to automatically produce reliable and repeatable decisions. Today's machine learning algorithms comb through data sets that no human could feasibly get through in a year or even a lifetime's worth of work. As the IoT continues to grow, more algorithms will be needed to keep up with the rising sums of data that accompany this growth. One of the main challenges of the IoT security is the integration with communication, computing, control, and physical environment parameters to analyse, detect and defend cyber-attacks in the distributed IoT systems.

The 4th International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIOT 2023) is an international conference dedicated to promoting novel theoretical and applied research advances in the interdisciplinary agenda of Internet of things. This special issue includes selected papers (with no less than 60% new content of the journal version) from SPIoT 2023, Oct. 20-21, 2023, Fuyang, Anhui, as well as an open call.

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 Editor

Jinghua Zhao, University of Shanghai for Science and Technology, China, zhaojinghua@usst.edu.cn (this opens in a new tab)

Important Dates

Manuscript Due:             30th October 2024
First Round of Reviews:  15th December 2024
Final Decision:                30th January 2025

Peer Review Process

All the papers will go through peer review,  and will be reviewed by at least two reviewers. A thorough check will be completed, and the guest editor 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. Previously published 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 to be considered for this special issue (with at least 60% difference from the original works).

Submission Guidelines

Paper submissions for the special issue should strictly follow the submission format and guidelines (https://www.springer.com/journal/521/submission-guidelines (this opens in a new tab)). Each manuscript should not exceed 16 pages in length (inclusive of figures and tables).

Manuscripts must be submitted to the journal online system at https://www.editorialmanager.com/ncaa/default.aspx (this opens in a new tab) or via the 'Submit manuscript' button on the journal homepage.
Authors should select “TC: ML and Big Data Analytics for IoT Security and Privacy (SPIOT 2023)” during the submission step ‘Additional Information’.

Author Resources

Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by other journals.  
Springer provides a host of information about publishing in a Springer Journal on our Journal Author Resources page, including  FAQs (this opens in a new tab),  Tutorials (this opens in a new tab)  along with  Help and Support (this opens in a new tab).
Other links include:

Search

Navigation