Engineering and Applied Sciences

Special Issue

Artificial Intelligence Security, Privacy, Trustworthiness-enhancing Techniques for AI-enabled Industrial Internet of Things

  • Submission Deadline: 1 June 2022
  • Status: Submission Closed
  • Lead Guest Editor: Jiwei Zhang
About This Special Issue
The Industrial Internet of Things (IIoT) is a network of physical objects including manufacturing and energy management, which can be used in interconnected sensors, instruments, and industrial applications. The IIoT is an evolution of a distributed control system that allows for a higher degree of automation by using cloud computing to refine and optimize the process of control, communication, computation and security. One of the key drivers of IIoT is the collection of massive data. So how to ensure the security, privacy, and trustworthiness of massive data collection, storage, and processing deeply impacts the success and stability of the IIoT.
The development of Artificial Intelligence (AI) has brought new opportunities in improving the efficiency of IIoT. The AI model can be learned from multi-source data; however the data source can be hacked, corrupted, or even malicious, which leads to destroying the performance of the AI model. So it is crucial how to build a secure, privacy-protected, and trustworthy framework to avoid undergoing adversarial attacks, leaking user data’s privacy, and fragile reliability. Emerging technologies such as distributed ledger technology, differential privacy, and federated learning have shown promising performance in the data security, privacy, and trustworthiness era. Recent advances of these emerging technologies can help mitigate the security, privacy, and trustworthiness challenges and redesign the framework of the IIoT.
This Special Issue aims to provide a platform for researchers to present novel and effective security, privacy, trustworthiness-enhancing techniques for AI-enabled IIoT. Original research and review articles are welcome.
Potential topics include but are not limited to the following:
(1) Data security, privacy, and trustworthiness in IIoT
(2) Detection and prevention of threats and attacks for AI-enabled IIoT
(3) Differential privacy for IIoT data
(4) Hardware and software security for IIoT
(5) Privacy-preserving machine learning for IIoT
(6) Blockchain-based scheme for IIoT
(7) Resource allocation optimization for AI-enabled IIoT
(8) Robust machine learning technology for IIoT
(9) Trustworthy smart contract for IIoT
(10) Secure wireless communications for IIoT
(11) Intelligent technology for human security in IIoT
(12) Modelling, analysis, simulation of data for IIoT
(13) Secure and trustworthy computing for IIoT

Keywords:

  1. Artificial Intelligence
  2. information security
  3. privacy protection
  4. trustworthiness
  5. Industrial Internet of Things
  6. machine learning
Lead Guest Editor
  • Jiwei Zhang

    School of Computer Science (National Pilot Software Engineering School), Beijing university of posts and telecommunications, Beijing, China