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Fast handover authentication scheme in 5G mobile edge computing scenarios
Published 2022-06-01Get full text
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Adversarial example defense algorithm for MNIST based on image reconstruction
Published 2022-02-01“…With the popularization of deep learning, more and more attention has been paid to its security issues.The adversarial sample is to add a small disturbance to the original image, which can cause the deep learning model to misclassify the image, which seriously affects the performance of deep learning technology.To address this challenge, the attack form and harm of the existing adversarial samples were analyzed.An adversarial examples defense method based on image reconstruction was proposed to effectively detect adversarial examples.The defense method used MNIST as the test data set.The core idea was image reconstruction, including central variance minimization and image quilting optimization.The central variance minimization was only processed for the central area of the image.The image quilting optimization incorporated the overlapping area into the patch block selection.Considered and took half the size of the patch as the overlap area.Using FGSM, BIM, DeepFool and C＆amp;W attack methods to generate adversarial samples to test the defense performance of the two methods, and compare with the existing three image reconstruction defense methods (cropping and scaling, bit depth compression and JPEG compression).The experimental results show that the central variance minimization and image quilting optimization algorithms proposed have a satisfied defense effect against the attacks of existing common adversarial samples.Image quilting optimization achieves over 75% classification accuracy for samples generated by the four attack algorithms, and the defense effect of minimizing central variance is around 70%.The three image reconstruction algorithms used for comparison have unstable defense effects on different attack algorithms, and the overall classification accuracy rate is less than 60%.The central variance minimization and image quilting optimization proposed achieve the purpose of effectively defending against adversarial samples.The experiments illustrate the defense effect of the proposed defense algorithm in different adversarial sample attack algorithms.The comparison between the reconstruction algorithm and the algorithm shows that the proposed scheme has good defense performance.…”
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Design and application of a general connector for drainage tube (一种引流管通用连接器的设计与应用)
Published 2024-11-01“…This paper introduces the design and use method of a utility model general connector for drainage tube, which is simple in structure and convenient in use, and can effectively improve the drainage effect and improve the work efficiency of medical staff by rinsing. …”
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Setting of residue definitions and toxicological reference values for ethiprole
Published 2024-12-01“…The residue definition for enforcement was derived as ‘ethiprole’. Adequate analytical methods for enforcement are available to control the residues of ethiprole in dry commodities at the validated LOQ of 0.002 mg/kg. …”
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