Currently, big data handling and its security have become a new, hot research topic among academics and the industry community. The new machine learning (especially deep learning) and optimization techniques are very essential tools for data analysis and ensuring data security. However, there are still numerous technical challenges and issues involving new machine learning models and optimization techniques that need to be improved and broadly explored for data analysis and security. For example, explainable deep learning models, zero-shot deep learning models, few-shot deep learning models, efficient global optimization methods for deep learning models, big data analysis and data and network security.
This Special Issue aims to provide the last and most innovative research on all theoretical and practical aspects in new machine learning techniques and optimization methods for data analysis, and data and network security.
The topics of interest include, but are not limited to:
- Models and methods of new deep learning
- New deep learning theory
- Explainable deep learning models
- Machine learning algorithm in networks
- Data mining for network data
- New optimization methods for data analysis
- Optimization models on resource allocation in wireless communications
- Optimization models on task scheduling in wireless communications
- New models on 5G and 6G networks
- Integration of AI and wireless or next generation networks
- Evolutionary algorithms for data analytical problems
- Security techniques in next generation networks
- Security techniques for data analytics
- Security techniques and AI for data analytics
- Computer network and Security
- Other related topics.
