The role of authigenic clay growth in clay gouge is increasingly recognized as a key to understanding the mechanics of berittle faulting and fault zone processes,including creep and seismogenesis,and providing new ins...The role of authigenic clay growth in clay gouge is increasingly recognized as a key to understanding the mechanics of berittle faulting and fault zone processes,including creep and seismogenesis,and providing new insights into the ongoing debate about the frictional strength of brittle fault(Haines and van der Pluijm,2012).However,neither the conditions nor the processes which展开更多
Adding subtle perturbations to an image can cause the classification model to misclassify,and such images are called adversarial examples.Adversar-ial examples threaten the safe use of deep neural networks,but when com...Adding subtle perturbations to an image can cause the classification model to misclassify,and such images are called adversarial examples.Adversar-ial examples threaten the safe use of deep neural networks,but when combined with reversible data hiding(RDH)technology,they can protect images from being correctly identified by unauthorized models and recover the image lossless under authorized models.Based on this,the reversible adversarial example(RAE)is ris-ing.However,existing RAE technology focuses on feasibility,attack success rate and image quality,but ignores transferability and time complexity.In this paper,we optimize the data hiding structure and combine data augmentation technology,whichflips the input image in probability to avoid overfitting phenomenon on the dataset.On the premise of maintaining a high success rate of white-box attacks and the image’s visual quality,the proposed method improves the transferability of reversible adversarial examples by approximately 16%and reduces the com-putational cost by approximately 43%compared to the state-of-the-art method.In addition,the appropriateflip probability can be selected for different application scenarios.展开更多
基金financed by the National Youth Sciences Foundation of China (No. 41502044)
文摘The role of authigenic clay growth in clay gouge is increasingly recognized as a key to understanding the mechanics of berittle faulting and fault zone processes,including creep and seismogenesis,and providing new insights into the ongoing debate about the frictional strength of brittle fault(Haines and van der Pluijm,2012).However,neither the conditions nor the processes which
基金This research work is partly supported by the National Natural Science Foundation of China(62172001)the Provincial Colleges Quality Project of Anhui Province(2020xsxxkc047)the National Undergraduate Innovation and Entrepreneurship Training Program(202210357077).
文摘Adding subtle perturbations to an image can cause the classification model to misclassify,and such images are called adversarial examples.Adversar-ial examples threaten the safe use of deep neural networks,but when combined with reversible data hiding(RDH)technology,they can protect images from being correctly identified by unauthorized models and recover the image lossless under authorized models.Based on this,the reversible adversarial example(RAE)is ris-ing.However,existing RAE technology focuses on feasibility,attack success rate and image quality,but ignores transferability and time complexity.In this paper,we optimize the data hiding structure and combine data augmentation technology,whichflips the input image in probability to avoid overfitting phenomenon on the dataset.On the premise of maintaining a high success rate of white-box attacks and the image’s visual quality,the proposed method improves the transferability of reversible adversarial examples by approximately 16%and reduces the com-putational cost by approximately 43%compared to the state-of-the-art method.In addition,the appropriateflip probability can be selected for different application scenarios.
