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In communications, innovative paradigm shifts have emerged in integrating various devices into the network to provide advanced and intelligent services. However, various security threats may occur that may not always be detected using traditional cryptographic techniques. Secure authentication is of paramount importance in modern wireless systems. This paper focusses on robust authentication in a timevarying communication environment where conventional authentication mechanisms are severely limited. We propose an Adaptive Neural Network (ANN) as an intelligent authentication process to improve detection accuracy. Specifically, a Data-Adaptive Matrix (DAM) is designed to track time-varying channel features. By utilizing a convolutional neural network as an intelligent authenticator, the proposed approach integrates deep feature extraction and attack detection, hence, leading to effective physical layer security. To evaluate the system, the ANN is prototyped on a universal software radio peripheral (USRP) and its authentication performance is evaluated in a conference room environment. Experimental results show that the ANN is effective in tackling the challenges of physical layer authentication under interference conditions, and is effective in time-varying environments. INDEX TERMS Convolutional neural network, physical layer security, intrusion detection, machine learning.

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Recently, information centric wireless network (ICWN) has been concerned due to its flexible network structure and high efficiency of content delivery. Meanwhile, scalable video coding (SVC) is a promising solution to provide high quality of video services. Combining ICWN and SVC is expected to improve the performance of wireless video delivery services. Since caching strategy plays a significant role in ICWN, in this paper, we address the caching problem for scalable videos over ICWN in mobile scenarios. By jointly considering the layered structure of SVC and the hierarchical architecture of ICWN, we formulate an optimization problem to minimize the average download delay. A novel layered hierarchical caching method is proposed for solving the problem. Furthermore, we focus on a special but common case in which the above delay minimization problem is equivalently transformed into a cache hit ratio maximization problem. A simplified algorithm with 1/2 approximation ratio is provided. Finally, simulation results show that our proposed caching schemes outperform baseline methods in cache hit rate and delay performance.INDEX TERMS ICWN, SVC, wireless caching, video transmission.

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