Current Issue : January-March Volume : 2023 Issue Number : 1 Articles : 5 Articles
In the Internet age, information security is threatened anytime and anywhere and the copyright protection of audio and video as well as the need for matching detection is increasingly strong. In view of this need, this paper proposes a zero-watermarking algorithm for audio and video matching based on NSCT. The algorithm uses NSCT, DCT, SVD, and Schur decomposition to extract video features and audio features and generates zero-watermark stream through synthesis, which is stored in a third-party organization for detection and identification. The detection algorithm can obtain zero watermark from the audio and video to be tested and judge and locate tampering by comparing with the zero watermark of the third party. From the experimental results, this algorithm can not only detect whether the audio and video are mismatched due to tampering attacks but also locate the mismatched audio and video segments and protect the copyright....
An explosion of traffic volume is the main driver behind launching various 5G services. The 5G network will utilize the IP Multimedia Subsystems (IMS) as a core network, same as in 4G networks. Thus, ensuring a high level of survivability and efficient failure management in the IMS is crucial before launching 5G services. We introduce a new methodology based on machine learning to predict the call failures occurring inside the IMS network using the traces for the Session Initiation Protocol (SIP) communication. Predicting that the call will fail enables the operator to prevent the failure by redirecting the call to another radio access technique by initiating the Circuit Switching fallback (CS-fallback) through a 380 SIP error response sent to the handset. The advantage of the model is not limited to call failure prediction, but also to know the root causes behind the failure; more specifically, the multi-factorial root is caused by using machine learning, which cannot be obtained using the traditional method (manual tracking of the traces). We built eight different machine learning models using four different classifiers (decision tree, naive Bayes, K-Nearest Neighbor (KNN), and Support Vector Machine (SVM)) and two different feature selection methods (Filter andWrapper). Finally, we compare the different models and use the one with the highest prediction accuracy to obtain the root causes beyond the call failures. The results demonstrate that using SVM classifier withWrapper feature selection method conducts the highest prediction accuracy, reaching 97.5%....
How to deal with the increasing video traffic and diverse service demands while ensuring the security of transmission is an open issue in the multimedia Internet of Things (IoT). This paper addresses this issue and studies a secure delivery scheme under a multicast scenario in the presence of multiple eavesdroppers where small base stations (SBSs) can send videos to users cooperatively. Aiming at potential eavesdroppers, a channel model including artificial noise is introduced to reduce the harm of illegal data acquisition. A network quality of experience (QoE) optimization problem is first formulated to account for video quality and delivery delay. In order to solve the nonconvex problem, the successive convex approximation (SCA) technique is applied to optimize multicast group beamforming, reduce the possibility of multicast video eavesdropping, and select video quality where a heuristic scheme is proposed to maximize the network QoE. The effectiveness of the proposed scheme is finally validated by extensive simulations in terms of algorithm convergence performance and network QoE-enhanced performance....
With the recent advances in computing devices such as smartphones and laptops, most devices are equipped with multiple network interfaces such as cellular, Wi-Fi, and Ethernet. Multipath TCP (MPTCP) has been the de facto standard for utilizing multipaths, and Multipath QUIC (MPQUIC), which is an extension of the Quick UDP Internet Connections (QUIC) protocol, has become a promising replacement due to its various advantages. The multipath scheduler, which determines the path to which each packet should be transmitted, is a key function that affects the multipath transport performance. For example, the default minRTT scheduler typically achieves good throughput, while the redundant scheduler gains low latency. While the legacy schedulers may generally give a desirable performance in some environments, however, each application renders different requirements. For example, Web applications target low latency, while video streaming applications require low jitter and high video quality. In this paper, we propose a novel MPQUIC scheduler based on deep reinforcement learning using the Deep Q-Network (DQN) that enhances the quality of multimedia streaming. Our proposal first takes into account both delay and throughput as a reward for reinforcement learning to achieve a low video chunk download time. Second, we propose a chunk manager that informs the scheduler of the video chunk information, and we also tune the learning parameters to explore new random actions adequately. Finally, we implement our new scheduler on the Linux kernel and give results using the Mininet experiments. The evaluation results show that our proposal outperforms legacy schedulers by at least 20%....
The in-depth development of the multimedia era has caused network video marketing to gradually penetrate into social production and daily life, and the network self-media platform has also played its own advantageous hand and established links in the creation of a new network video marketing model, highlighting the important role of the network self-media platform. To this end, this article analyzes the current situation of video marketing in the multimedia era and combines a variety of marketing tools such as trends, implantation, and emotions to optimize the transformation in promotion by analyzing new marketing strategies while promoting sustainable development of enterprises. On this basis, this article explores and analyzes the impact of video marketing on consumer psychology and behavior in the multimedia era....
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