With the advancement of smart grid transformation, the configuration audit of distribution network communication networks faces challenges such as diversified network devices, numerous manufacturers, and multi-source ...
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Deception detection is gaining increasing interest due to ethical and security concerns. This paper explores the application of convolutional neural networks for the purpose of multimodal deception detection. We use a...
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The capacity to analyze the causes of poor decisions made by visual recognition models is becoming increasingly crucial as the security requirements of various real-world systems continue to escalate. However, the com...
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ISBN:
(纸本)9798350359329;9798350359312
The capacity to analyze the causes of poor decisions made by visual recognition models is becoming increasingly crucial as the security requirements of various real-world systems continue to escalate. However, the complex structure and blackbox nature within deep neural networks constrain the mining of their error causes. Based on this, we propose a conceptbased (e.g. a group of pixel blocks that contain leaves represents the concept of leaves) automated strong localization interpretation framework, called hierarchically optimized concept-sensitive interpretation (HOCS), to provide quantitative analysis of the semantics of wrong decisions in the classification network is provided from two directions of internal and external information interference of samples. HOCS was applied to models with spurious correlation and well-distributed data in the training set. The results showed that it provided concrete explanations in a way that was understandable to humans and demonstrated the significant advantages of HOCS in terms of efficiency and accuracy.
The digital world of today is always evolving;hence strong cybersecurity measures are more crucial than before. Conventional cybersecurity defences frequently fall short in identifying and countering sophisticated cyb...
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IoT security poses a significant challenge due to the presence of extensive confidential data and vulnerable devices. Artificial intelligence (AI) is increasingly viewed as pivotal in cybersecurity, enhancing the effi...
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This paper introduces a novel real-time intrusion detection approach for UAV networks, addressing current security challenges. We leverage Generative Adversarial networks (GANs) to generate synthetic data and implemen...
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Domain Name systems (DNS) are crucial components of any modern network, as they allow users to type in a domain name as opposed to complete IP addresses to visit web pages on the internet. The DNS resolution process t...
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Recently, cyberattacks on IoT (Internet of Things) and IIoT (Industrial Internet of Things) networks have become increasingly complicated and more frequent. These attacks have posed considerable threats such as Distri...
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Perfect power flow methods can be employed to choose which inverters will supply and determine their optimal real and reactive power settings based on financial goals. Utilizing advanced semidefinite relaxation make p...
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Ensemble techniques could find DDoS attacks more quickly in IoT. A more dependable and precise detection system can be achieved by integrating the most advantageous attributes of XGBoost and Random Forest. This ensure...
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