With the rise of network cameras, the authenticity of video data they capture has become a common challenge in forensic science and expertise. There are many camera manufacturers and brands available, and videos from ...
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This work proposes a novel and efficient quad-stream BiLSTM-Attention network, abbreviated as QSLA network, for robust automatic modulation classification (AMC) of wireless signals. The proposed model exploits multipl...
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ISBN:
(纸本)9798350350463;9798350350456
This work proposes a novel and efficient quad-stream BiLSTM-Attention network, abbreviated as QSLA network, for robust automatic modulation classification (AMC) of wireless signals. The proposed model exploits multiple representations of the wireless signal as inputs to the network and the feature extraction process combines convolutional and BiLSTM layers for processing the spatial and temporal features of the signal, respectively. An attention layer is used after the BiLSTM layer to emphasize the important temporal features. The experimental results on the recent and realistic RML22 dataset demonstrate the superior performance of the proposed model with an accuracy up to around 99%. The model is compared with other benchmark models in the literature in terms of classification accuracy, computational complexity, memory usage, and training time to show the effectiveness of our proposed approach.
In this paper, the introduction of big data technology, from the hardware and software two aspects of communication security protection system design research. With the support of hardware equipment, the secure commun...
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Malicious attackers frequently aim to partition the network into disjointed segments to facilitate specific attacks. Consequently, enhancing network reliability stands as an effective preventive measure. Connectivity ...
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ISBN:
(纸本)9798350349184;9798350349191
Malicious attackers frequently aim to partition the network into disjointed segments to facilitate specific attacks. Consequently, enhancing network reliability stands as an effective preventive measure. Connectivity serves as a crucial metric for gauging network reliability, yet classical connectivity inadequately captures a network's fault tolerance in the face of such attacks. To address this, cluster connectivity has been proposed, considering the faults within clusters to improve fault tolerance assessment. In this paper, we establish the cluster connectivity of the half hypercube network HHn. In detail, we show that the K-1,K-1-cluster connectivity of HHn is left perpendicularn/2right perpendicular + 1, where n >= 3, and the K-1,K-r-cluster connectivity of HHn is inverted right perpendicularn/2inverted left perpendicular/2 + 1, where n >= 5 and 2 <= r <= 4, which is almost r times the classical connectivity. This indicates that the network possesses an enhanced capacity to accommodate a greater number of faulty nodes, potentially enabling more effective orchestration of attacks.
Visualizing the complex relationship among enterprises is ponderable to help enterprises and institutions to find potential risks. Small and medium-size enterprises' (SMEs) loans have higher risk and non-performin...
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ISBN:
(纸本)9783031500749;9783031500756
Visualizing the complex relationship among enterprises is ponderable to help enterprises and institutions to find potential risks. Small and medium-size enterprises' (SMEs) loans have higher risk and non-performing rates than other types of enterprises, which are prone to form the complex relationship. Nowadays, the analysis of enterprises' relationships networks mainly focus on the guaranteed relationships among enterprises, but it lacks the holistic analysis of the enterprise community of interest. To address these issues, the concepts of the enterprise community of interest and the investment model withing enterprise community of interest are proposed;The centrality, density, and network diameter algorithms in graph theory are used to evaluate the network of enterprise community of interest;The problem of graph isomorphism are used to query the network of users interested enterprises' relationships;The portrait of enterprise is used to evaluate the enterprise community of interest;In the end, we study the impact of debt relationship among enterprise community of interest. Based on these ideas, to verify the effectiveness of the method, an enterprise relationship network analysis system which included 6745 enterprise nodes and 7435 enterprise relationship data of Shanghai is developed.
This article addresses the issues of low efficiency and fragmented processes in network security incident response, proposing an innovative solution that utilizes security orchestration technology to optimize the hand...
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Based on the design concept of "human-computer collaboration", this research aims to design intelligent college English teaching assistants with the core goal of promoting the deep integration of technical w...
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User identification is explored through EEG-based biometric analysis using different auditory stimuli, using the distinctiveness and security of EEG signals for reliable biometric authentication. The impact on system ...
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Co-resident attacks in the cloud environment have always been a concern. Different from other network attacks, it is a cache-based side-channel attack. Many studies have shown that it can be co-located with the target...
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In situations when the precise position of a machine is unknown,localization becomes *** research focuses on improving the position prediction accuracy over long-range(LoRa)network using an optimized machine learning-...
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In situations when the precise position of a machine is unknown,localization becomes *** research focuses on improving the position prediction accuracy over long-range(LoRa)network using an optimized machine learning-based *** order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting method over LoRa technology,this study proposed an optimized machine learning(ML)based *** signal strength indicator(RSSI)data from the sensors at different positions was first gathered via an experiment through the LoRa network in a multistory round layout *** noise factor is also taken into account,and the signal-to-noise ratio(SNR)value is recorded for every RSSI *** study concludes the examination of reference point accuracy with the modified KNN method(MKNN).MKNN was created to more precisely anticipate the position of the reference *** findings showed that MKNN outperformed other algorithms in terms of accuracy and complexity.
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