Computer Science ›› 2022, Vol. 49 ›› Issue (10): 285-290.doi: 10.11896/jsjkx.210900254
• Information Security • Previous Articles Next Articles
YANG Wen-bo, YUAN Ji-dong
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[1]SZEGEDY C,ZAREMBA W,SUTSKEVER I,et al.Intriguing properties of neural networks [J].arXiv:1312.6199,2013. [2]EYKHOLT K,EVTIMOV I,FERNANDES E,et al.Robustphysical-world attacks on deep learning visual classification[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.IEEE,2018. [3]ZHANG W E,SHENG Q Z,ALHAZMI A,et al.Adversarial attacks on deep-learning models in natural language processing:A survey [J].ACM Transactions on Intelligent Systems and Technology(TIST),2020,11(3):1-41. [4]DANG-NHU R,SINGH G,BIELIK P,et al.Adversarial attacks on probabilistic autoregressive forecasting models[C]//Procee-dings of the International Conference on Machine Learning.PMLR,2020. [5]ZHENG Z,YANG Y,NIU X,et al.Wide and deep convolutional neural networks for electricity-theft detection to secure smart grids [J].IEEE Transactions on Industrial Informatics,2017,14(4):1606-1615. [6]FAWAZ H I,FORESTIER G,WEBER J,et al.Adversarial attacks on deep neural networks for time series classification[C]//Proceedings of the 2019 International Joint Conference on Neural Networks(IJCNN).IEEE,2019. [7]CHEN H,HUANG C,HUANG Q,et al.Ecgadv:Generatingadversarial electrocardiogram to misguide arrhythmia classification system[C]//Proceedings of the AAAI Conference on Artificial Intelligence.AAAI,2020. [8]PAPERNOT N,MCDANIEL P,GOODFELLOW I,et al.Practical black-box attacks against machine learning[C]//Procee-dings of the 2017 ACM on Asia Conference on Computer and Communications Security.ACM,2017. [9]SU J,VARGAS D V,SAKURAI K.One pixel attack for fooling deep neural networks [J].IEEE Transactions on Evolutionary Computation,2019,23(5):828-841. [10]OREGI I,DEL SER J,PEREZ A,et al.Adversarial sample crafting for time series classification with elastic similarity measures[C]//Proceedings of the International Symposium on Intelligent and Distributed Computing.Springer,2018. [11]KARIM F,MAJUMDAR S,DARABI H.Adversarial attacks on time series [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2020,43(10):3309-3320. [12]YE L,KEOGH E.Time series shapelets:a new primitive for data mining[C]//Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.ACM,2009. [13]DAU H A,BAGNALL A,KAMGAR K,et al.The UCR time series archive [J].IEEE/CAA Journal of Automatica Sinica,2019,6(6):1293-1305. [14]PAN W W,WANG X Y,SONG M L,et al.Survey on Generating Adversarial Examples [J].Journal of Software,2020,31(1):67-81. [15]PAPERNOT N,MCDANIEL P,GOODFELLOW I.Transferability in machine learning:from phenomena to black-box attacks using adversarial samples [J].arXiv:1605.07277,2016. [16]SARKAR S,BANSAL A,MAHBUB U,et al.UPSET and ANGRI:Breaking high performance image classifiers [J].arXiv:1707.01159,2017. [17]RATHORE P,BASAK A,NISTALA S H,et al.Untargeted,Targeted and Universal Adversarial Attacks and Defenses on Time Series[C]//Proceedings of the 2020 International Joint Conference on Neural Networks(IJCNN).IEEE,2020. [18]HARFORD S,KARIM F,DARABI H.Adversarial attacks on multivariate time series [J].arXiv:2004.00410,2020. [19]HAN X,HU Y,FOSCHINI L,et al.Deep learning models forelectrocardiograms are susceptible to adversarial attack [J].Nature Medicine,2020,26(3):360-363. [20]JI G L.Survey on genetic algorithm [J].Computer Applications and Software,2004,21(2):69-73. [21]ANDERSON E J,FERRIS M C.Genetic algorithms for combinatorial optimization:the assemble line balancing problem [J].ORSA Journal on Computing,1994,6(2):161-173. [22]YAN W H,LI G L.Research on time series classification based on shapelet [J].Computer Science,2019,46(1):29-35. [23]WANG Z,YAN W,OATES T.Time series classification from scratch with deep neural networks:A strong baseline[C]//Proceedings of the 2017 International Joint Conference on Neural Networks(IJCNN).IEEE,2017. [24]IOFFE S,SZEGEDY C.Batch normalization:Accelerating deep network training by reducing internal covariate shift[C]//Proceedings of the International Conference on Machine Learning.PMLR,2015. [25]KRIZHEVSKY A,SUTSKEVER I,HINTON G E.Imagenetclassification with deep convolutional neural networks [J].Advances in Neural Information Processing Systems,2012,25:1097-1105. [26]DEMš AR J.Statistical comparisons of classifiers over multiple data sets [J].The Journal of Machine Learning Research,2006,7:1-30. |
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