Статті в журналах з теми "White-box attack"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся з топ-50 статей у журналах для дослідження на тему "White-box attack".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Переглядайте статті в журналах для різних дисциплін та оформлюйте правильно вашу бібліографію.
Chen, Jinghui, Dongruo Zhou, Jinfeng Yi, and Quanquan Gu. "A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 3486–94. http://dx.doi.org/10.1609/aaai.v34i04.5753.
Повний текст джерелаJosse, Sébastien. "White-box attack context cryptovirology." Journal in Computer Virology 5, no. 4 (August 2, 2008): 321–34. http://dx.doi.org/10.1007/s11416-008-0097-x.
Повний текст джерелаPorkodi, V., M. Sivaram, Amin Salih Mohammed, and V. Manikandan. "Survey on White-Box Attacks and Solutions." Asian Journal of Computer Science and Technology 7, no. 3 (November 5, 2018): 28–32. http://dx.doi.org/10.51983/ajcst-2018.7.3.1904.
Повний текст джерелаALSHEKH, MOKHTAR, and KÖKSAL ERENTÜRK. "DEFENSE AGAINST WHITE BOX ADVERSARIAL ATTACKS IN ARABIC NATURAL LANGUAGE PROCESSING (ANLP)." International Journal of Advanced Natural Sciences and Engineering Researches 7, no. 6 (July 25, 2023): 151–55. http://dx.doi.org/10.59287/ijanser.1149.
Повний текст джерелаPark, Hosung, Gwonsang Ryu, and Daeseon Choi. "Partial Retraining Substitute Model for Query-Limited Black-Box Attacks." Applied Sciences 10, no. 20 (October 14, 2020): 7168. http://dx.doi.org/10.3390/app10207168.
Повний текст джерелаZhou, Jie, Jian Bai, and Meng Shan Jiang. "White-Box Implementation of ECDSA Based on the Cloud Plus Side Mode." Security and Communication Networks 2020 (November 19, 2020): 1–10. http://dx.doi.org/10.1155/2020/8881116.
Повний текст джерелаLIN, Ting-Ting, and Xue-Jia LAI. "Efficient Attack to White-Box SMS4 Implementation." Journal of Software 24, no. 8 (January 17, 2014): 2238–49. http://dx.doi.org/10.3724/sp.j.1001.2013.04356.
Повний текст джерелаZhang, Sicheng, Yun Lin, Zhida Bao, and Jiangzhi Fu. "A Lightweight Modulation Classification Network Resisting White Box Gradient Attacks." Security and Communication Networks 2021 (October 12, 2021): 1–10. http://dx.doi.org/10.1155/2021/8921485.
Повний текст джерелаGao, Xianfeng, Yu-an Tan, Hongwei Jiang, Quanxin Zhang, and Xiaohui Kuang. "Boosting Targeted Black-Box Attacks via Ensemble Substitute Training and Linear Augmentation." Applied Sciences 9, no. 11 (June 3, 2019): 2286. http://dx.doi.org/10.3390/app9112286.
Повний текст джерелаJiang, Yi, and Dengpan Ye. "Black-Box Adversarial Attacks against Audio Forensics Models." Security and Communication Networks 2022 (January 17, 2022): 1–8. http://dx.doi.org/10.1155/2022/6410478.
Повний текст джерелаLee, Xian Yeow, Sambit Ghadai, Kai Liang Tan, Chinmay Hegde, and Soumik Sarkar. "Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 4577–84. http://dx.doi.org/10.1609/aaai.v34i04.5887.
Повний текст джерелаChitic, Raluca, Ali Osman Topal, and Franck Leprévost. "Empirical Perturbation Analysis of Two Adversarial Attacks: Black Box versus White Box." Applied Sciences 12, no. 14 (July 21, 2022): 7339. http://dx.doi.org/10.3390/app12147339.
Повний текст джерелаDionysiou, Antreas, Vassilis Vassiliades, and Elias Athanasopoulos. "Exploring Model Inversion Attacks in the Black-box Setting." Proceedings on Privacy Enhancing Technologies 2023, no. 1 (January 2023): 190–206. http://dx.doi.org/10.56553/popets-2023-0012.
Повний текст джерелаDu, Xiaohu, Jie Yu, Zibo Yi, Shasha Li, Jun Ma, Yusong Tan, and Qinbo Wu. "A Hybrid Adversarial Attack for Different Application Scenarios." Applied Sciences 10, no. 10 (May 21, 2020): 3559. http://dx.doi.org/10.3390/app10103559.
Повний текст джерелаDuan, Mingxing, Kenli Li, Jiayan Deng, Bin Xiao, and Qi Tian. "A Novel Multi-Sample Generation Method for Adversarial Attacks." ACM Transactions on Multimedia Computing, Communications, and Applications 18, no. 4 (November 30, 2022): 1–21. http://dx.doi.org/10.1145/3506852.
Повний текст джерелаFu, Zhongwang, and Xiaohui Cui. "ELAA: An Ensemble-Learning-Based Adversarial Attack Targeting Image-Classification Model." Entropy 25, no. 2 (January 22, 2023): 215. http://dx.doi.org/10.3390/e25020215.
Повний текст джерелаChen, Yiding, and Xiaojin Zhu. "Optimal Attack against Autoregressive Models by Manipulating the Environment." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 3545–52. http://dx.doi.org/10.1609/aaai.v34i04.5760.
Повний текст джерелаTu, Chun-Chen, Paishun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, and 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 (July 17, 2019): 742–49. http://dx.doi.org/10.1609/aaai.v33i01.3301742.
Повний текст джерелаUsoltsev, Yakov, Balzhit Lodonova, Alexander Shelupanov, Anton Konev, and Evgeny Kostyuchenko. "Adversarial Attacks Impact on the Neural Network Performance and Visual Perception of Data under Attack." Information 13, no. 2 (February 5, 2022): 77. http://dx.doi.org/10.3390/info13020077.
Повний текст джерелаFang, Yong, Cheng Huang, Yijia Xu, and Yang Li. "RLXSS: Optimizing XSS Detection Model to Defend Against Adversarial Attacks Based on Reinforcement Learning." Future Internet 11, no. 8 (August 14, 2019): 177. http://dx.doi.org/10.3390/fi11080177.
Повний текст джерелаWei, Zhipeng, Jingjing Chen, Zuxuan Wu, and Yu-Gang Jiang. "Boosting the Transferability of Video Adversarial Examples via Temporal Translation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 3 (June 28, 2022): 2659–67. http://dx.doi.org/10.1609/aaai.v36i3.20168.
Повний текст джерелаChang, Heng, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Wenwu Zhu, and Junzhou Huang. "A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 3389–96. http://dx.doi.org/10.1609/aaai.v34i04.5741.
Повний текст джерелаPark, Sanglee, and Jungmin So. "On the Effectiveness of Adversarial Training in Defending against Adversarial Example Attacks for Image Classification." Applied Sciences 10, no. 22 (November 14, 2020): 8079. http://dx.doi.org/10.3390/app10228079.
Повний текст джерелаWon, Jongho, Seung-Hyun Seo, and Elisa Bertino. "A Secure Shuffling Mechanism for White-Box Attack-Resistant Unmanned Vehicles." IEEE Transactions on Mobile Computing 19, no. 5 (May 1, 2020): 1023–39. http://dx.doi.org/10.1109/tmc.2019.2903048.
Повний текст джерелаPedersen, Joseph, Rafael Muñoz-Gómez, Jiangnan Huang, Haozhe Sun, Wei-Wei Tu, and Isabelle Guyon. "LTU Attacker for Membership Inference." Algorithms 15, no. 7 (July 20, 2022): 254. http://dx.doi.org/10.3390/a15070254.
Повний текст джерелаGomez-Alanis, Alejandro, Jose A. Gonzalez-Lopez, and Antonio M. Peinado. "GANBA: Generative Adversarial Network for Biometric Anti-Spoofing." Applied Sciences 12, no. 3 (January 29, 2022): 1454. http://dx.doi.org/10.3390/app12031454.
Повний текст джерелаCroce, Francesco, Maksym Andriushchenko, Naman D. Singh, Nicolas Flammarion, and Matthias Hein. "Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 6 (June 28, 2022): 6437–45. http://dx.doi.org/10.1609/aaai.v36i6.20595.
Повний текст джерелаHuang, Yang, Yuling Chen, Xuewei Wang, Jing Yang, and Qi Wang. "Promoting Adversarial Transferability via Dual-Sampling Variance Aggregation and Feature Heterogeneity Attacks." Electronics 12, no. 3 (February 3, 2023): 767. http://dx.doi.org/10.3390/electronics12030767.
Повний текст джерелаRiadi, Imam, Rusydi Umar, Iqbal Busthomi, and Arif Wirawan Muhammad. "Block-hash of blockchain framework against man-in-the-middle attacks." Register: Jurnal Ilmiah Teknologi Sistem Informasi 8, no. 1 (May 15, 2021): 1. http://dx.doi.org/10.26594/register.v8i1.2190.
Повний текст джерелаCombey, Théo, António Loison, Maxime Faucher, and Hatem Hajri. "Probabilistic Jacobian-Based Saliency Maps Attacks." Machine Learning and Knowledge Extraction 2, no. 4 (November 13, 2020): 558–78. http://dx.doi.org/10.3390/make2040030.
Повний текст джерелаDing, Daizong, Mi Zhang, Fuli Feng, Yuanmin Huang, Erling Jiang, and Min Yang. "Black-Box Adversarial Attack on Time Series Classification." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 6 (June 26, 2023): 7358–68. http://dx.doi.org/10.1609/aaai.v37i6.25896.
Повний текст джерелаJin, Di, Bingdao Feng, Siqi Guo, Xiaobao Wang, Jianguo Wei, and Zhen Wang. "Local-Global Defense against Unsupervised Adversarial Attacks on Graphs." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 7 (June 26, 2023): 8105–13. http://dx.doi.org/10.1609/aaai.v37i7.25979.
Повний текст джерелаDas, Debayan, Santosh Ghosh, Arijit Raychowdhury, and Shreyas Sen. "EM/Power Side-Channel Attack: White-Box Modeling and Signature Attenuation Countermeasures." IEEE Design & Test 38, no. 3 (June 2021): 67–75. http://dx.doi.org/10.1109/mdat.2021.3065189.
Повний текст джерелаWang, Yixiang, Jiqiang Liu, Xiaolin Chang, Ricardo J. Rodríguez, and Jianhua Wang. "DI-AA: An interpretable white-box attack for fooling deep neural networks." Information Sciences 610 (September 2022): 14–32. http://dx.doi.org/10.1016/j.ins.2022.07.157.
Повний текст джерелаKoga, Kazuki, and Kazuhiro Takemoto. "Simple Black-Box Universal Adversarial Attacks on Deep Neural Networks for Medical Image Classification." Algorithms 15, no. 5 (April 22, 2022): 144. http://dx.doi.org/10.3390/a15050144.
Повний текст джерелаDas, Debayan, and Shreyas Sen. "Electromagnetic and Power Side-Channel Analysis: Advanced Attacks and Low-Overhead Generic Countermeasures through White-Box Approach." Cryptography 4, no. 4 (October 31, 2020): 30. http://dx.doi.org/10.3390/cryptography4040030.
Повний текст джерелаYang, Zhifei, Wenmin Li, Fei Gao, and Qiaoyan Wen. "FAPA: Transferable Adversarial Attacks Based on Foreground Attention." Security and Communication Networks 2022 (October 29, 2022): 1–8. http://dx.doi.org/10.1155/2022/4447307.
Повний текст джерелаHaq, Ijaz Ul, Zahid Younas Khan, Arshad Ahmad, Bashir Hayat, Asif Khan, Ye-Eun Lee, and Ki-Il Kim. "Evaluating and Enhancing the Robustness of Sustainable Neural Relationship Classifiers Using Query-Efficient Black-Box Adversarial Attacks." Sustainability 13, no. 11 (May 24, 2021): 5892. http://dx.doi.org/10.3390/su13115892.
Повний текст джерелаLi, Chenwei, Hengwei Zhang, Bo Yang, and Jindong Wang. "Image classification adversarial attack with improved resizing transformation and ensemble models." PeerJ Computer Science 9 (July 25, 2023): e1475. http://dx.doi.org/10.7717/peerj-cs.1475.
Повний текст джерелаLin, Gengyou, Zhisong Pan, Xingyu Zhou, Yexin Duan, Wei Bai, Dazhi Zhan, Leqian Zhu, Gaoqiang Zhao, and Tao Li. "Boosting Adversarial Transferability with Shallow-Feature Attack on SAR Images." Remote Sensing 15, no. 10 (May 22, 2023): 2699. http://dx.doi.org/10.3390/rs15102699.
Повний текст джерелаZhang, Chao, and Yu Wang. "Research on the Structure of Authentication Protocol Analysis Based on MSCs/Promela." Advanced Materials Research 989-994 (July 2014): 4698–703. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4698.
Повний текст джерелаZhang, Yue, Seong-Yoon Shin, Xujie Tan, and Bin Xiong. "A Self-Adaptive Approximated-Gradient-Simulation Method for Black-Box Adversarial Sample Generation." Applied Sciences 13, no. 3 (January 18, 2023): 1298. http://dx.doi.org/10.3390/app13031298.
Повний текст джерелаGuo, Lu, and Hua Zhang. "A white-box impersonation attack on the FaceID system in the real world." Journal of Physics: Conference Series 1651 (November 2020): 012037. http://dx.doi.org/10.1088/1742-6596/1651/1/012037.
Повний текст джерелаShi, Yang, Qin Liu, and 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.
Повний текст джерелаLiu, Zhenpeng, Ruilin Li, Dewei Miao, Lele Ren, and Yonggang Zhao. "Membership Inference Defense in Distributed Federated Learning Based on Gradient Differential Privacy and Trust Domain Division Mechanisms." Security and Communication Networks 2022 (July 14, 2022): 1–14. http://dx.doi.org/10.1155/2022/1615476.
Повний текст джерелаWang, Fangwei, Yuanyuan Lu, Changguang Wang, and Qingru Li. "Binary Black-Box Adversarial Attacks with Evolutionary Learning against IoT Malware Detection." Wireless Communications and Mobile Computing 2021 (August 30, 2021): 1–9. http://dx.doi.org/10.1155/2021/8736946.
Повний текст джерелаMao, Junjie, Bin Weng, Tianqiang Huang, Feng Ye, and Liqing Huang. "Research on Multimodality Face Antispoofing Model Based on Adversarial Attacks." Security and Communication Networks 2021 (August 9, 2021): 1–12. http://dx.doi.org/10.1155/2021/3670339.
Повний текст джерелаSuri, Anshuman, and David Evans. "Formalizing and Estimating Distribution Inference Risks." Proceedings on Privacy Enhancing Technologies 2022, no. 4 (October 2022): 528–51. http://dx.doi.org/10.56553/popets-2022-0121.
Повний текст джерелаHwang, Ren-Hung, Jia-You Lin, Sun-Ying Hsieh, Hsuan-Yu Lin, and Chia-Liang Lin. "Adversarial Patch Attacks on Deep-Learning-Based Face Recognition Systems Using Generative Adversarial Networks." Sensors 23, no. 2 (January 11, 2023): 853. http://dx.doi.org/10.3390/s23020853.
Повний текст джерелаSun, Jiazheng, Li Chen, Chenxiao Xia, Da Zhang, Rong Huang, Zhi Qiu, Wenqi Xiong, Jun Zheng, and Yu-An Tan. "CANARY: An Adversarial Robustness Evaluation Platform for Deep Learning Models on Image Classification." Electronics 12, no. 17 (August 30, 2023): 3665. http://dx.doi.org/10.3390/electronics12173665.
Повний текст джерела