Preface to Special Issue on AI-Based Future Intelligent Networks and Communication Security

Recent advancements in science focus on the study and development of algorithms that can learn from and make predictions and decisions based on data collected through intelligent devices. Big data analytics, AI, and software defined networking help to drive the management of data and usage of the e...

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Bibliographic Details
Main Authors: Sunil Kumar, Glenford Mapp, Abhay Bansal, Korhan Cengiz
Format: Article
Language:English
Published: Institute of Fundamental Technological Research Polish Academy of Sciences 2024-09-01
Series:Computer Assisted Methods in Engineering and Science
Subjects:
Online Access:https://cames.ippt.pan.pl/index.php/cames/article/view/1742
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Summary:Recent advancements in science focus on the study and development of algorithms that can learn from and make predictions and decisions based on data collected through intelligent devices. Big data analytics, AI, and software defined networking help to drive the management of data and usage of the exceptional computational power provided by cloud computing. This special issue explores novel concepts and cutting-edge research and developments aimed at designing fully automated advanced digital networks. Driven by technological advances in big data, AI, and ML, such systems potentially have a wide range of applications in networking and communication security. The special issue covers analytical techniques for handling the vast amount of data generated by the Internet of Things (IoT), addressing topics ranging from architectures and platforms to security and privacy issues, applications, and challenges as well as future directions. Next-generation protocols will dynamically learn and train themselves to improve reliability, fault tolerance, security, and storage optimization in cloud. These new concepts will allow network algorithms to ‘learn’ and change elastically based on the information they are exposed to. This issue comprises four outstanding contributions.
ISSN:2299-3649
2956-5839