METHODS AND SYSTEMS OF INFORMATION PROTECTION, INFORMATION SECURITY
Ensuring security of data processing and transmission in promising wireless communication systems at the design stage using deep machine learning based on artificial intelligence
Abstract:
Ensuring the security of data processing and transmission in advanced high-speed wireless communication systems is one of the priority tasks. This paper demonstrates that machine learning is widely used in the design of such systems at the upper layers of wireless communication systems. However, its application at the physical layer is hampered by complex channel environments and the limited learning capabilities of algorithms that describe the changing data transmission channel. This paper presents examples of applying deep machine learning methods at the physical layer to various wireless communication systems. Methods for creating a new architecture for remote access systems based on machine learning using an autoencoder are proposed. It is shown that the application of deep learning with artificial intelligence at the physical layer of wireless communication systems can facilitate the design of complex scenarios with unknown data transmission channel models. Algorithms based on deep machine learning with artificial intelligence demonstrate competitive performance with lower complexity or latency. They may find potential application in advanced secure high-speed, interference-resistant communication systems.
