Deep learning has developed rapidly and made significant breakthroughs in many areas, such as artificial intelligence, data management, and resource allocation. Meanwhile, when addressing security problems, especially security problems for multimedia in communication and mobile networks, deep learning techniques face a large number of issues, such as huge computation power costs, unstable communications, and volatile mobile networks.

With the increase of data scales in multimedia, deep learning models are likely to contain tens of billions of parameters. What is more challenging is that it is hard to perform pruning in communication and mobile networks. To improve the training efficiency of deep learning models for multimedia security, investigating the distributed or parallel learning techniques is required. For example, it is valuable to study the scheduling strategy for multiple working nodes during the training of deep learning models for multimedia security in communication and mobile networks.

In this Special Issue, we seek research on deep learning for multimedia security in communication and mobile networks. This Special Issue focuses on recent advances in architecture, algorithms, optimization, tools, and models for deep learning in multimedia security. We encourage original research and review articles that reflect various aspects of the advancements in deep learning for multimedia security.

Potential topics include but are not limited to the following:

• Deep learning for multimedia security in communication and mobile networks
• Deep learning for hypermedia security in communication and mobile networks
• Fault tolerance in multimedia and hypermedia systems using deep learning techniques
• Privacy preservation using deep learning in multimedia and hypermedia systems
• Secure collaborative computing for multimedia and hypermedia in communication and mobile networks
• Adversarial learning in multimedia and hypermedia systems
• Parallel deep learning for multimedia security in communication and mobile networks
• Large-scale security analysis using deep learning for multimedia and hypermedia
• Resource allocation and scheduling of deep learning for multimedia security
• Data protection using deep learning for multimedia and hypermedia security
• Surveys of security using deep learning for multimedia and hypermedia
• Future challenges for deep learning-driven multimedia and hypermedia security