Submission Deadline: 15 October 2022 (closed) View: 141
In modern industries, the Internet of Things (IoT) is used to collect real-time data from many sensors and actuators. The widespread adoption of the IoT in modern organisations is transforming current industry trends in terms of data gathering, analysis, and effective monitoring of industrial activities. Through intelligent decision-making and remote management, the IoT can improve the smart industry's production and efficiency. The rapid expansion of IoT networks, on the other hand, may raise security and privacy concerns. In the domain of cybersecurity, the analysis of security and privacy issues in the IoT, as well as potential solutions to solve these challenges, has become a hot topic. Machine learning (ML) and deep learning (DL) approaches have been applied in IoT applications for a number of security solutions in recent years. Because of their superior pattern extraction skills, ML and DL algorithms have received a lot of attention in recent studies compared to traditional learning methods. Because IoT devices are resource-constrained, modern IoT networks require lightweight security solutions. In this regard, we encourage academics to submit original research articles as well as review articles that will aim to explore novel solutions for IoT networks.
Scope:
We welcome high-quality articles on one or more of the following themes to be submitted:
Intrusion detection in the Internet of Things (IoT)
Trends in industrial IoT security and privacy
Lightweight multimedia encryption
Lightweight encryption for IoT
Edge computing, edge security
Blockchain for IoT
Artificial Intelligence for IoT
Cryptography for IoT
Image encryption for IoT applications