Security and Communication Networks

Privacy and Security of Information Processing in Industrial Big Data and Internet of Things

Publishing date
01 Aug 2019
Submission deadline
15 Mar 2019

1Hubei University of Technology, Wuhan, China

2University of Missouri-Kansas City, Kansas City, USA

3University of Electronic Science and Technology, Chengdu, China

This issue is now closed for submissions.
More articles will be published in the near future.

Privacy and Security of Information Processing in Industrial Big Data and Internet of Things

This issue is now closed for submissions.
More articles will be published in the near future.


With the development of technologies in Internet of Things and Cloud Computing, big data has been focused and applied to almost every industry, retail, healthcare, financial services, government, and so on. Particularly for the era of Industrial 4.0 and industrial Internet of Things (iIoT), more and more data gathering devices and communication technologies are implemented, leading to the new information-processing requirement of volume, variety, velocity, and veracity for industrial big data. The iIoT allows people and things to be connected anyplace, anytime, with anything and anyone using any network and any service. However, such procedures can also lead to node or user privacy issues.

Privacy and security issues during big-data processing in industrial Internet-of-Things age did receive significant attention over the last few years. Although industrial big data has potential to stimulate plenty of applications in future, considerable technical issues are challenging and need to be solved. Firstly, privacy leakage in volume of industrial big data is considered with various structures by multiple types of devices communicating with each other.

Interoperability, real-time processing and action lead the security threats in integrating heterogeneous data during data analysis and decision-making. Malicious attacks may occur anytime anywhere in the whole iIoT system, and users’ privacy may be exposed and threatened. Therefore, the security and privacy are crucial issues during data processing and transmission in every level of Industrial 4.0 and iIoT frameworks. Precaution against security attacks and privacy protection via novel security-aware techniques are imperious needs for researchers in academia and industry.

This issue aims to discuss some of the main challenges of security and privacy in information-processing in iIoT and opportunities for current research and innovation. We welcome research and review articles on the state of the art in industrial big-data processing and securing in Industrial 4.0 and iIoT. Particularly, we are soliciting theoretical and applied research including protocols, algorithms, technologies, and applications.

Potential topics include but are not limited to the following:

  • Models and algorithms for the security and privacy in Industrial 4.0, iIoT, and industrial big data
  • Infrastructures for secure big-data acquisition, storage, and transmission for iIoT
  • Privacy-preserving solutions to outsourced data processing in iIoT
  • Security and privacy-based schemes and protocols in Industrial 4.0 and iIoT
  • Privacy-preserving analytic and predictive models for industrial big data
  • Security and privacy for the convergence of heterogeneous industrial data
  • Intelligent models and algorithms for secure optimization, control, and automation
  • Node/user privacy in industrial Internet of Things
  • Secure and efficient hardware, devices, and designs for Internet of Things
  • Privacy-preserving machine learning and deep learning in industrial-level data process and control
  • Secure data analysis and diagnostics for real-time reporting in the industrial clouds
Security and Communication Networks
Publishing Collaboration
More info
Wiley Hindawi logo
 Journal metrics
Acceptance rate31%
Submission to final decision85 days
Acceptance to publication42 days
Journal Citation Indicator0.370
Impact Factor1.791

Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.