Network Security in Artificial Intelligence Systems, 2nd Edition

Dear Colleagues,

AI network security refers to the measures taken to protect artificial intelligence (AI) systems and their networks from unauthorized access, theft, damage, and disruption. With the increasing use of AI in various industries and applications, the need for secure AI networks has become more critical. This is due to the sensitive nature of AI data (big data), which may contain confidential information, as well as the potential consequences of AI systems being compromised, such as the loss of data, reduced system availability, and reputational damage, among others. Encryption is one of the most important methods used in AI network security. Another important method is the use of firewalls, which are hardware or software systems that block unauthorized access to a network. Firewalls can be configured to allow only approved traffic to enter the network, reducing the risk of cyberattacks.

Intrusion detection and prevention systems are also used in AI network security. These systems monitor network activity and identify suspicious behavior, allowing administrators to respond quickly to potential threats. Access control systems, which limit access to sensitive data based on user roles and permissions, are another important aspect of AI network security. By ensuring that only authorized users can access sensitive data, the risk of unauthorized access or theft is reduced. Editors are invited to submit original and high-quality papers on the application of network security in artificial intelligence systems.

Dr. Chi-Yao Weng
Dr. Shoko Wakamiya
Prof. Dr. Chun-Ta Li
Dr. Cheng-Ta Huang
Guest Editors

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