Artículos de revistas sobre el tema "White-box attack"
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Chen, Jinghui, Dongruo Zhou, Jinfeng Yi y Quanquan Gu. "A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 3486–94. http://dx.doi.org/10.1609/aaai.v34i04.5753.
Texto completoJosse, Sébastien. "White-box attack context cryptovirology". Journal in Computer Virology 5, n.º 4 (2 de agosto de 2008): 321–34. http://dx.doi.org/10.1007/s11416-008-0097-x.
Texto completoPorkodi, V., M. Sivaram, Amin Salih Mohammed y V. Manikandan. "Survey on White-Box Attacks and Solutions". Asian Journal of Computer Science and Technology 7, n.º 3 (5 de noviembre de 2018): 28–32. http://dx.doi.org/10.51983/ajcst-2018.7.3.1904.
Texto completoALSHEKH, MOKHTAR y KÖKSAL ERENTÜRK. "DEFENSE AGAINST WHITE BOX ADVERSARIAL ATTACKS IN ARABIC NATURAL LANGUAGE PROCESSING (ANLP)". International Journal of Advanced Natural Sciences and Engineering Researches 7, n.º 6 (25 de julio de 2023): 151–55. http://dx.doi.org/10.59287/ijanser.1149.
Texto completoPark, Hosung, Gwonsang Ryu y Daeseon Choi. "Partial Retraining Substitute Model for Query-Limited Black-Box Attacks". Applied Sciences 10, n.º 20 (14 de octubre de 2020): 7168. http://dx.doi.org/10.3390/app10207168.
Texto completoZhou, Jie, Jian Bai y Meng Shan Jiang. "White-Box Implementation of ECDSA Based on the Cloud Plus Side Mode". Security and Communication Networks 2020 (19 de noviembre de 2020): 1–10. http://dx.doi.org/10.1155/2020/8881116.
Texto completoLIN, Ting-Ting y Xue-Jia LAI. "Efficient Attack to White-Box SMS4 Implementation". Journal of Software 24, n.º 8 (17 de enero de 2014): 2238–49. http://dx.doi.org/10.3724/sp.j.1001.2013.04356.
Texto completoZhang, Sicheng, Yun Lin, Zhida Bao y Jiangzhi Fu. "A Lightweight Modulation Classification Network Resisting White Box Gradient Attacks". Security and Communication Networks 2021 (12 de octubre de 2021): 1–10. http://dx.doi.org/10.1155/2021/8921485.
Texto completoGao, Xianfeng, Yu-an Tan, Hongwei Jiang, Quanxin Zhang y Xiaohui Kuang. "Boosting Targeted Black-Box Attacks via Ensemble Substitute Training and Linear Augmentation". Applied Sciences 9, n.º 11 (3 de junio de 2019): 2286. http://dx.doi.org/10.3390/app9112286.
Texto completoJiang, Yi y Dengpan Ye. "Black-Box Adversarial Attacks against Audio Forensics Models". Security and Communication Networks 2022 (17 de enero de 2022): 1–8. http://dx.doi.org/10.1155/2022/6410478.
Texto completoLee, Xian Yeow, Sambit Ghadai, Kai Liang Tan, Chinmay Hegde y Soumik Sarkar. "Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 4577–84. http://dx.doi.org/10.1609/aaai.v34i04.5887.
Texto completoChitic, Raluca, Ali Osman Topal y Franck Leprévost. "Empirical Perturbation Analysis of Two Adversarial Attacks: Black Box versus White Box". Applied Sciences 12, n.º 14 (21 de julio de 2022): 7339. http://dx.doi.org/10.3390/app12147339.
Texto completoDionysiou, Antreas, Vassilis Vassiliades y Elias Athanasopoulos. "Exploring Model Inversion Attacks in the Black-box Setting". Proceedings on Privacy Enhancing Technologies 2023, n.º 1 (enero de 2023): 190–206. http://dx.doi.org/10.56553/popets-2023-0012.
Texto completoDu, Xiaohu, Jie Yu, Zibo Yi, Shasha Li, Jun Ma, Yusong Tan y Qinbo Wu. "A Hybrid Adversarial Attack for Different Application Scenarios". Applied Sciences 10, n.º 10 (21 de mayo de 2020): 3559. http://dx.doi.org/10.3390/app10103559.
Texto completoDuan, Mingxing, Kenli Li, Jiayan Deng, Bin Xiao y Qi Tian. "A Novel Multi-Sample Generation Method for Adversarial Attacks". ACM Transactions on Multimedia Computing, Communications, and Applications 18, n.º 4 (30 de noviembre de 2022): 1–21. http://dx.doi.org/10.1145/3506852.
Texto completoFu, Zhongwang y Xiaohui Cui. "ELAA: An Ensemble-Learning-Based Adversarial Attack Targeting Image-Classification Model". Entropy 25, n.º 2 (22 de enero de 2023): 215. http://dx.doi.org/10.3390/e25020215.
Texto completoChen, Yiding y Xiaojin Zhu. "Optimal Attack against Autoregressive Models by Manipulating the Environment". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 3545–52. http://dx.doi.org/10.1609/aaai.v34i04.5760.
Texto completoTu, Chun-Chen, Paishun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh y Shin-Ming Cheng. "AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 742–49. http://dx.doi.org/10.1609/aaai.v33i01.3301742.
Texto completoUsoltsev, Yakov, Balzhit Lodonova, Alexander Shelupanov, Anton Konev y Evgeny Kostyuchenko. "Adversarial Attacks Impact on the Neural Network Performance and Visual Perception of Data under Attack". Information 13, n.º 2 (5 de febrero de 2022): 77. http://dx.doi.org/10.3390/info13020077.
Texto completoFang, Yong, Cheng Huang, Yijia Xu y Yang Li. "RLXSS: Optimizing XSS Detection Model to Defend Against Adversarial Attacks Based on Reinforcement Learning". Future Internet 11, n.º 8 (14 de agosto de 2019): 177. http://dx.doi.org/10.3390/fi11080177.
Texto completoWei, Zhipeng, Jingjing Chen, Zuxuan Wu y Yu-Gang Jiang. "Boosting the Transferability of Video Adversarial Examples via Temporal Translation". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 3 (28 de junio de 2022): 2659–67. http://dx.doi.org/10.1609/aaai.v36i3.20168.
Texto completoChang, Heng, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Wenwu Zhu y Junzhou Huang. "A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 3389–96. http://dx.doi.org/10.1609/aaai.v34i04.5741.
Texto completoPark, Sanglee y Jungmin So. "On the Effectiveness of Adversarial Training in Defending against Adversarial Example Attacks for Image Classification". Applied Sciences 10, n.º 22 (14 de noviembre de 2020): 8079. http://dx.doi.org/10.3390/app10228079.
Texto completoWon, Jongho, Seung-Hyun Seo y Elisa Bertino. "A Secure Shuffling Mechanism for White-Box Attack-Resistant Unmanned Vehicles". IEEE Transactions on Mobile Computing 19, n.º 5 (1 de mayo de 2020): 1023–39. http://dx.doi.org/10.1109/tmc.2019.2903048.
Texto completoPedersen, Joseph, Rafael Muñoz-Gómez, Jiangnan Huang, Haozhe Sun, Wei-Wei Tu y Isabelle Guyon. "LTU Attacker for Membership Inference". Algorithms 15, n.º 7 (20 de julio de 2022): 254. http://dx.doi.org/10.3390/a15070254.
Texto completoGomez-Alanis, Alejandro, Jose A. Gonzalez-Lopez y Antonio M. Peinado. "GANBA: Generative Adversarial Network for Biometric Anti-Spoofing". Applied Sciences 12, n.º 3 (29 de enero de 2022): 1454. http://dx.doi.org/10.3390/app12031454.
Texto completoCroce, Francesco, Maksym Andriushchenko, Naman D. Singh, Nicolas Flammarion y Matthias Hein. "Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 6 (28 de junio de 2022): 6437–45. http://dx.doi.org/10.1609/aaai.v36i6.20595.
Texto completoHuang, Yang, Yuling Chen, Xuewei Wang, Jing Yang y Qi Wang. "Promoting Adversarial Transferability via Dual-Sampling Variance Aggregation and Feature Heterogeneity Attacks". Electronics 12, n.º 3 (3 de febrero de 2023): 767. http://dx.doi.org/10.3390/electronics12030767.
Texto completoRiadi, Imam, Rusydi Umar, Iqbal Busthomi y Arif Wirawan Muhammad. "Block-hash of blockchain framework against man-in-the-middle attacks". Register: Jurnal Ilmiah Teknologi Sistem Informasi 8, n.º 1 (15 de mayo de 2021): 1. http://dx.doi.org/10.26594/register.v8i1.2190.
Texto completoCombey, Théo, António Loison, Maxime Faucher y Hatem Hajri. "Probabilistic Jacobian-Based Saliency Maps Attacks". Machine Learning and Knowledge Extraction 2, n.º 4 (13 de noviembre de 2020): 558–78. http://dx.doi.org/10.3390/make2040030.
Texto completoDing, Daizong, Mi Zhang, Fuli Feng, Yuanmin Huang, Erling Jiang y Min Yang. "Black-Box Adversarial Attack on Time Series Classification". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 6 (26 de junio de 2023): 7358–68. http://dx.doi.org/10.1609/aaai.v37i6.25896.
Texto completoJin, Di, Bingdao Feng, Siqi Guo, Xiaobao Wang, Jianguo Wei y Zhen Wang. "Local-Global Defense against Unsupervised Adversarial Attacks on Graphs". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 7 (26 de junio de 2023): 8105–13. http://dx.doi.org/10.1609/aaai.v37i7.25979.
Texto completoDas, Debayan, Santosh Ghosh, Arijit Raychowdhury y Shreyas Sen. "EM/Power Side-Channel Attack: White-Box Modeling and Signature Attenuation Countermeasures". IEEE Design & Test 38, n.º 3 (junio de 2021): 67–75. http://dx.doi.org/10.1109/mdat.2021.3065189.
Texto completoWang, Yixiang, Jiqiang Liu, Xiaolin Chang, Ricardo J. Rodríguez y Jianhua Wang. "DI-AA: An interpretable white-box attack for fooling deep neural networks". Information Sciences 610 (septiembre de 2022): 14–32. http://dx.doi.org/10.1016/j.ins.2022.07.157.
Texto completoKoga, Kazuki y Kazuhiro Takemoto. "Simple Black-Box Universal Adversarial Attacks on Deep Neural Networks for Medical Image Classification". Algorithms 15, n.º 5 (22 de abril de 2022): 144. http://dx.doi.org/10.3390/a15050144.
Texto completoDas, Debayan y Shreyas Sen. "Electromagnetic and Power Side-Channel Analysis: Advanced Attacks and Low-Overhead Generic Countermeasures through White-Box Approach". Cryptography 4, n.º 4 (31 de octubre de 2020): 30. http://dx.doi.org/10.3390/cryptography4040030.
Texto completoYang, Zhifei, Wenmin Li, Fei Gao y Qiaoyan Wen. "FAPA: Transferable Adversarial Attacks Based on Foreground Attention". Security and Communication Networks 2022 (29 de octubre de 2022): 1–8. http://dx.doi.org/10.1155/2022/4447307.
Texto completoHaq, Ijaz Ul, Zahid Younas Khan, Arshad Ahmad, Bashir Hayat, Asif Khan, Ye-Eun Lee y Ki-Il Kim. "Evaluating and Enhancing the Robustness of Sustainable Neural Relationship Classifiers Using Query-Efficient Black-Box Adversarial Attacks". Sustainability 13, n.º 11 (24 de mayo de 2021): 5892. http://dx.doi.org/10.3390/su13115892.
Texto completoLi, Chenwei, Hengwei Zhang, Bo Yang y Jindong Wang. "Image classification adversarial attack with improved resizing transformation and ensemble models". PeerJ Computer Science 9 (25 de julio de 2023): e1475. http://dx.doi.org/10.7717/peerj-cs.1475.
Texto completoLin, Gengyou, Zhisong Pan, Xingyu Zhou, Yexin Duan, Wei Bai, Dazhi Zhan, Leqian Zhu, Gaoqiang Zhao y Tao Li. "Boosting Adversarial Transferability with Shallow-Feature Attack on SAR Images". Remote Sensing 15, n.º 10 (22 de mayo de 2023): 2699. http://dx.doi.org/10.3390/rs15102699.
Texto completoZhang, Chao y Yu Wang. "Research on the Structure of Authentication Protocol Analysis Based on MSCs/Promela". Advanced Materials Research 989-994 (julio de 2014): 4698–703. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4698.
Texto completoZhang, Yue, Seong-Yoon Shin, Xujie Tan y Bin Xiong. "A Self-Adaptive Approximated-Gradient-Simulation Method for Black-Box Adversarial Sample Generation". Applied Sciences 13, n.º 3 (18 de enero de 2023): 1298. http://dx.doi.org/10.3390/app13031298.
Texto completoGuo, Lu y Hua Zhang. "A white-box impersonation attack on the FaceID system in the real world". Journal of Physics: Conference Series 1651 (noviembre de 2020): 012037. http://dx.doi.org/10.1088/1742-6596/1651/1/012037.
Texto completoShi, Yang, Qin Liu y Qinpei Zhao. "A Secure Implementation of a Symmetric Encryption Algorithm in White-Box Attack Contexts". Journal of Applied Mathematics 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/431794.
Texto completoLiu, Zhenpeng, Ruilin Li, Dewei Miao, Lele Ren y Yonggang Zhao. "Membership Inference Defense in Distributed Federated Learning Based on Gradient Differential Privacy and Trust Domain Division Mechanisms". Security and Communication Networks 2022 (14 de julio de 2022): 1–14. http://dx.doi.org/10.1155/2022/1615476.
Texto completoWang, Fangwei, Yuanyuan Lu, Changguang Wang y Qingru Li. "Binary Black-Box Adversarial Attacks with Evolutionary Learning against IoT Malware Detection". Wireless Communications and Mobile Computing 2021 (30 de agosto de 2021): 1–9. http://dx.doi.org/10.1155/2021/8736946.
Texto completoMao, Junjie, Bin Weng, Tianqiang Huang, Feng Ye y Liqing Huang. "Research on Multimodality Face Antispoofing Model Based on Adversarial Attacks". Security and Communication Networks 2021 (9 de agosto de 2021): 1–12. http://dx.doi.org/10.1155/2021/3670339.
Texto completoSuri, Anshuman y David Evans. "Formalizing and Estimating Distribution Inference Risks". Proceedings on Privacy Enhancing Technologies 2022, n.º 4 (octubre de 2022): 528–51. http://dx.doi.org/10.56553/popets-2022-0121.
Texto completoHwang, Ren-Hung, Jia-You Lin, Sun-Ying Hsieh, Hsuan-Yu Lin y Chia-Liang Lin. "Adversarial Patch Attacks on Deep-Learning-Based Face Recognition Systems Using Generative Adversarial Networks". Sensors 23, n.º 2 (11 de enero de 2023): 853. http://dx.doi.org/10.3390/s23020853.
Texto completoSun, Jiazheng, Li Chen, Chenxiao Xia, Da Zhang, Rong Huang, Zhi Qiu, Wenqi Xiong, Jun Zheng y Yu-An Tan. "CANARY: An Adversarial Robustness Evaluation Platform for Deep Learning Models on Image Classification". Electronics 12, n.º 17 (30 de agosto de 2023): 3665. http://dx.doi.org/10.3390/electronics12173665.
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