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Titlebook: Cyberspace Safety and Security; 12th International S Jieren Cheng,Xiangyan Tang,Xiaozhang Liu Conference proceedings 2021 Springer Nature S

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,A Semi-supervised Learning Approach for High Dimensional Android Malware Classification,includes a random projection method for reducing feature dimensionality which would be more efficient than usual feature selection methods in existing work for the task. We also introduced a new method of SGD-based SVM with adapted sampling, which was based on the insight from the confidence and nea
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Kernel Optimization in SVM for Defense Against Adversarial Attacks,h field of adversarial machine learning. Support vector machines (SVMs), as a kind of successful approach, were widely used to solve security problems, such as image classification, malware detection, spam filtering, and intrusion detection. However, many adversarial attack methods have emerged rece
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Reliability Optimization and Trust Computing of Composite Wing Based on Sparse PC Method,he research on uncertainty analysis method is particularly important. Although the traditional Monte Carlo method can ensure the accuracy of optimization, it takes too long time, which limits its potential application on engineering. High precision uncertainty analysis and optimization design based
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,A Robust Digital Watermarking for Medical Images Based on PHTs-DCT,ng algorithms are failed to solve the protection problems against geometric attacks. To solve this problem, a robust digital watermarking algorithm for medical images based on PHTs-DCT is proposed in this paper. For embedding watermark, DCT is applied to reduce the redundant data of the image, then
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A Robust Zero Watermarking Algorithm for Medical Images Based on Tetrolet-DCT, concerns about the privacy of patient information. Aiming at the hidden dangers of copying, cutting, tampering, etc. in the dissemination of medical images, combined with the characteristics of medical images, this paper proposed a novel zero-watermarking algorithm based on Tetrolet-DCT, focusing o
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