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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