While the MQTT protocol is widely adopted in IoT applications, its usage for Industrial IoT is prevented by the lack of support for time-critical transmissions. For this reason, recent work has proposed the Prioritize...
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Fast charging stations for electric vehicles (EVs) often consist of charging units with multiple modules connected in parallel to achieve high power ratings and can suffer from cyber-attacks in the modern smart grid a...
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Alzheimer's Disease is a complex and currently one of the most prevalent illnesses. Due to these factors there is a growing emphasis on the early diagnosis of Alzheimer's Disease and our approach involves leve...
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The two-dimensional problem of the reflection and transmission of a plane electromagnetic wave symmetrically incident from either the convex or the concave side on a parabolic-cylinder interface separating two differe...
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False data injection attack(FDIA)is an attack that affects the stability of grid cyber-physical system(GCPS)by evading the detecting mechanism of bad *** FDIA detection methods usually employ complex neural networkmod...
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False data injection attack(FDIA)is an attack that affects the stability of grid cyber-physical system(GCPS)by evading the detecting mechanism of bad *** FDIA detection methods usually employ complex neural networkmodels to detect FDIA ***,they overlook the fact that FDIA attack samples at public-private network edges are extremely sparse,making it difficult for neural network models to obtain sufficient samples to construct a robust detection *** address this problem,this paper designs an efficient sample generative adversarial model of FDIA attack in public-private network edge,which can effectively bypass the detectionmodel to threaten the power grid system.A generative adversarial network(GAN)framework is first constructed by combining residual networks(ResNet)with fully connected networks(FCN).Then,a sparse adversarial learning model is built by integrating the time-aligned data and normal data,which is used to learn the distribution characteristics between normal data and attack data through iterative ***,we introduce a Gaussian hybrid distributionmatrix by aggregating the network structure of attack data characteristics and normal data characteristics,which can connect and calculate FDIA data with normal ***,efficient FDIA attack samples can be sequentially generated through interactive adversarial *** simulation experiments are conducted with IEEE 14-bus and IEEE 118-bus system data,and the results demonstrate that the generated attack samples of the proposed model can present superior performance compared to state-of-the-art models in terms of attack strength,robustness,and covert capability.
Agricultural productivity has a critical role in maintaining economies, especially in nations where a significant proportion of the population is engaged in farming. Plant diseases are a serious risk to agricultural p...
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The transition away from fossil fuels due to their environmental impact has prompted the integration of renewable energy sources, particularly wind and solar, into the main grid. However, the intermittent nature of th...
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Digital reviews provide real-world feedback on products and services in an era of online commerce and access to information. Providing feedback fosters trust and credibility among potential customers, enabling them to...
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Cloud storage makes it easier for users to access and share data remotely, but it often requires integration with cryptographic technologies to address consumer-oriented applications, such as fine-grained data access,...
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Class-imbalanced datasets pose a significant challenge for classification tasks in supervised learning, as standard classification algorithms are designed under the assumption that the datasets have balanced class dis...
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