Статті в журналах з теми "Encrypted domain traffic classification"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся з топ-50 статей у журналах для дослідження на тему "Encrypted domain traffic classification".
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.
Akbari, Iman, Mohammad A. Salahuddin, Leni Ven, Noura Limam, Raouf Boutaba, Bertrand Mathieu, Stephanie Moteau, and Stephane Tuffin. "Traffic classification in an increasingly encrypted web." Communications of the ACM 65, no. 10 (October 2022): 75–83. http://dx.doi.org/10.1145/3559439.
Повний текст джерелаAkbari, Iman, Mohammad A. Salahuddin, Leni Ven, Noura Limam, Raouf Boutaba, Bertrand Mathieu, Stephanie Moteau, and Stephane Tuffin. "A Look Behind the Curtain: Traffic Classification in an Increasingly Encrypted Web." ACM SIGMETRICS Performance Evaluation Review 49, no. 1 (June 22, 2022): 23–24. http://dx.doi.org/10.1145/3543516.3453921.
Повний текст джерелаAkbari, Iman, Mohammad A. Salahuddin, Leni Ven, Noura Limam, Raouf Boutaba, Bertrand Mathieu, Stephanie Moteau, and Stephane Tuffin. "A Look Behind the Curtain: Traffic Classification in an Increasingly Encrypted Web." Proceedings of the ACM on Measurement and Analysis of Computing Systems 5, no. 1 (February 18, 2021): 1–26. http://dx.doi.org/10.1145/3447382.
Повний текст джерелаIliyasu, Auwal Sani, Ibrahim Abba, Badariyya Sani Iliyasu, and Abubakar Sadiq Muhammad. "A Review of Deep Learning Techniques for Encrypted Traffic Classification." Computational Intelligence and Machine Learning 3, no. 2 (October 14, 2022): 15–21. http://dx.doi.org/10.36647/ciml/03.02.a003.
Повний текст джерелаBakhshi, Taimur, and Bogdan Ghita. "Anomaly Detection in Encrypted Internet Traffic Using Hybrid Deep Learning." Security and Communication Networks 2021 (September 21, 2021): 1–16. http://dx.doi.org/10.1155/2021/5363750.
Повний текст джерелаDeng, Guoqiang, Min Tang, Yuhao Zhang, Ying Huang, and Xuefeng Duan. "Privacy-Preserving Outsourced Artificial Neural Network Training for Secure Image Classification." Applied Sciences 12, no. 24 (December 14, 2022): 12873. http://dx.doi.org/10.3390/app122412873.
Повний текст джерелаMeng, Yitong, and Jinlong Fei. "Hidden Service Website Response Fingerprinting Attacks Based on Response Time Feature." Security and Communication Networks 2020 (November 30, 2020): 1–21. http://dx.doi.org/10.1155/2020/8850472.
Повний текст джерелаHu, Xinyi, Chunxiang Gu, Yihang Chen, and Fushan Wei. "CBD: A Deep-Learning-Based Scheme for Encrypted Traffic Classification with a General Pre-Training Method." Sensors 21, no. 24 (December 9, 2021): 8231. http://dx.doi.org/10.3390/s21248231.
Повний текст джерелаBoldyrikhin, N. V., D. A. Korochentsev, and F. A. Altunin. "CLASSIFICATION FEATURES OF ENCRYPTED NETWORK TRAFFIC." IZVESTIYA SFedU. ENGINEERING SCIENCES, no. 3 (October 19, 2020): 89–98. http://dx.doi.org/10.18522/2311-3103-2020-3-89-98.
Повний текст джерелаLu, Bei, Nurbol Luktarhan, Chao Ding, and Wenhui Zhang. "ICLSTM: Encrypted Traffic Service Identification Based on Inception-LSTM Neural Network." Symmetry 13, no. 6 (June 17, 2021): 1080. http://dx.doi.org/10.3390/sym13061080.
Повний текст джерелаRoy, Sangita, Tal Shapira, and Yuval Shavitt. "Fast and lean encrypted Internet traffic classification." Computer Communications 186 (March 2022): 166–73. http://dx.doi.org/10.1016/j.comcom.2022.02.003.
Повний текст джерелаLi, Yan, and Yifei Lu. "ETCC: Encrypted Two-Label Classification Using CNN." Security and Communication Networks 2021 (March 8, 2021): 1–11. http://dx.doi.org/10.1155/2021/6633250.
Повний текст джерелаHuang, Yung-Fa, Chuan-Bi Lin, Chien-Min Chung, and Ching-Mu Chen. "Research on QoS Classification of Network Encrypted Traffic Behavior Based on Machine Learning." Electronics 10, no. 12 (June 8, 2021): 1376. http://dx.doi.org/10.3390/electronics10121376.
Повний текст джерелаYi, Junkai, Guanglin Gong, Zeyu Liu, and Yacong Zhang. "Classification of Markov Encrypted Traffic on Gaussian Mixture Model Constrained Clustering." Wireless Communications and Mobile Computing 2021 (October 7, 2021): 1–11. http://dx.doi.org/10.1155/2021/4935108.
Повний текст джерелаDong, Cong, Chen Zhang, Zhigang Lu, Baoxu Liu, and Bo Jiang. "CETAnalytics: Comprehensive effective traffic information analytics for encrypted traffic classification." Computer Networks 176 (July 2020): 107258. http://dx.doi.org/10.1016/j.comnet.2020.107258.
Повний текст джерелаde Toledo, Thais, and Nunzio Torrisi. "Encrypted DNP3 Traffic Classification Using Supervised Machine Learning Algorithms." Machine Learning and Knowledge Extraction 1, no. 1 (January 15, 2019): 384–99. http://dx.doi.org/10.3390/make1010022.
Повний текст джерелаShi, Zhaolei, Nurbol Luktarhan, Yangyang Song, and Gaoqi Tian. "BFCN: A Novel Classification Method of Encrypted Traffic Based on BERT and CNN." Electronics 12, no. 3 (January 19, 2023): 516. http://dx.doi.org/10.3390/electronics12030516.
Повний текст джерелаPathmaperuma, Madushi H., Yogachandran Rahulamathavan, Safak Dogan, and Ahmet Kondoz. "CNN for User Activity Detection Using Encrypted In-App Mobile Data." Future Internet 14, no. 2 (February 21, 2022): 67. http://dx.doi.org/10.3390/fi14020067.
Повний текст джерелаMa, Chencheng, Xuehui Du, and Lifeng Cao. "Improved KNN Algorithm for Fine-Grained Classification of Encrypted Network Flow." Electronics 9, no. 2 (February 13, 2020): 324. http://dx.doi.org/10.3390/electronics9020324.
Повний текст джерелаRezaei, Shahbaz, and Xin Liu. "Deep Learning for Encrypted Traffic Classification: An Overview." IEEE Communications Magazine 57, no. 5 (May 2019): 76–81. http://dx.doi.org/10.1109/mcom.2019.1800819.
Повний текст джерелаMishra, Ankur. "Encrypted network traffic classification with convolutional auto-encoders." International Journal of Information Systems and Management 2, no. 2 (2020): 139. http://dx.doi.org/10.1504/ijisam.2020.10032697.
Повний текст джерелаMishra, Ankur. "Encrypted network traffic classification with convolutional auto-encoders." International Journal of Information Systems and Management 2, no. 2 (2020): 139. http://dx.doi.org/10.1504/ijisam.2020.110551.
Повний текст джерелаZhuang Qiao, Shunliang Zhang, Liuqun Zhai, and Xiaohui Zhang. "Encrypted 5G over-the-top voice traffic classification using deep learning." ITU Journal on Future and Evolving Technologies 3, no. 3 (December 9, 2022): 779–92. http://dx.doi.org/10.52953/eyif3681.
Повний текст джерелаLiu, Xinlei. "Identification of Encrypted Traffic Using Advanced Mathematical Modeling and Computational Intelligence." Mathematical Problems in Engineering 2022 (August 22, 2022): 1–10. http://dx.doi.org/10.1155/2022/1419804.
Повний текст джерелаMa, Zhuhong, Kunyang Li, Zongyu Li, and Liu Yao. "Encrypted Traffic Classification Based on a Convolutional Neural Network." Journal of Physics: Conference Series 2400, no. 1 (December 1, 2022): 012056. http://dx.doi.org/10.1088/1742-6596/2400/1/012056.
Повний текст джерелаHa, Joonseo, and Heejun Roh. "Experimental Evaluation of Malware Family Classification Methods from Sequential Information of TLS-Encrypted Traffic." Electronics 10, no. 24 (December 20, 2021): 3180. http://dx.doi.org/10.3390/electronics10243180.
Повний текст джерелаChengjie GU, Shunyi ZHANG, and Xiaozhen XUE. "Encrypted Internet Traffic Classification Method based on Host Behavior." International Journal of Digital Content Technology and its Applications 5, no. 3 (March 31, 2011): 167–74. http://dx.doi.org/10.4156/jdcta.vol5.issue3.16.
Повний текст джерелаAceto, Giuseppe, Domenico Ciuonzo, Antonio Montieri, and Antonio Pescapé. "DISTILLER: Encrypted traffic classification via multimodal multitask deep learning." Journal of Network and Computer Applications 183-184 (June 2021): 102985. http://dx.doi.org/10.1016/j.jnca.2021.102985.
Повний текст джерелаAceto, Giuseppe, Domenico Ciuonzo, Antonio Montieri, and Antonio Pescapé. "Toward effective mobile encrypted traffic classification through deep learning." Neurocomputing 409 (October 2020): 306–15. http://dx.doi.org/10.1016/j.neucom.2020.05.036.
Повний текст джерелаAceto, Giuseppe, Domenico Ciuonzo, Antonio Montieri, and Antonio Pescapè. "MIMETIC: Mobile encrypted traffic classification using multimodal deep learning." Computer Networks 165 (December 2019): 106944. http://dx.doi.org/10.1016/j.comnet.2019.106944.
Повний текст джерелаCasino, Fran, Kim-Kwang Raymond Choo, and Constantinos Patsakis. "HEDGE: Efficient Traffic Classification of Encrypted and Compressed Packets." IEEE Transactions on Information Forensics and Security 14, no. 11 (November 2019): 2916–26. http://dx.doi.org/10.1109/tifs.2019.2911156.
Повний текст джерелаLi, Ying, Yi Huang, Suranga Seneviratne, Kanchana Thilakarathna, Adriel Cheng, Guillaume Jourjon, Darren Webb, David B. Smith, and Richard Yi Da Xu. "From traffic classes to content: A hierarchical approach for encrypted traffic classification." Computer Networks 212 (July 2022): 109017. http://dx.doi.org/10.1016/j.comnet.2022.109017.
Повний текст джерелаRen, Guoqiang, Guang Cheng, and Nan Fu. "Accurate Encrypted Malicious Traffic Identification via Traffic Interaction Pattern Using Graph Convolutional Network." Applied Sciences 13, no. 3 (January 23, 2023): 1483. http://dx.doi.org/10.3390/app13031483.
Повний текст джерелаPathmaperuma, Madushi H., Yogachandran Rahulamathavan, Safak Dogan, and Ahmet M. Kondoz. "Deep Learning for Encrypted Traffic Classification and Unknown Data Detection." Sensors 22, no. 19 (October 9, 2022): 7643. http://dx.doi.org/10.3390/s22197643.
Повний текст джерелаWang, Hong Zhi, and Li Hui Yan. "A New Network Traffic Classification Method Based on Optimized Hadamard Matrix and ECOC-SVM." Advanced Materials Research 989-994 (July 2014): 1895–900. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.1895.
Повний текст джерелаChen, Wenxiong, Feng Lyu, Fan Wu, Peng Yang, Guangtao Xue, and Minglu Li. "Sequential Message Characterization for Early Classification of Encrypted Internet Traffic." IEEE Transactions on Vehicular Technology 70, no. 4 (April 2021): 3746–60. http://dx.doi.org/10.1109/tvt.2021.3063738.
Повний текст джерелаVelan, Petr, Milan Čermák, Pavel Čeleda, and Martin Drašar. "A survey of methods for encrypted traffic classification and analysis." International Journal of Network Management 25, no. 5 (July 15, 2015): 355–74. http://dx.doi.org/10.1002/nem.1901.
Повний текст джерелаZhang, Xueqin, Min Zhao, Jiyuan Wang, Shuang Li, Yue Zhou, and Shinan Zhu. "Deep-Forest-Based Encrypted Malicious Traffic Detection." Electronics 11, no. 7 (March 22, 2022): 977. http://dx.doi.org/10.3390/electronics11070977.
Повний текст джерелаZheng, Juan, Zhiyong Zeng, and Tao Feng. "GCN-ETA: High-Efficiency Encrypted Malicious Traffic Detection." Security and Communication Networks 2022 (January 22, 2022): 1–11. http://dx.doi.org/10.1155/2022/4274139.
Повний текст джерелаSun, Weishi, Yaning Zhang, Jie Li, Chenxing Sun, and Shuzhuang Zhang. "A Deep Learning-Based Encrypted VPN Traffic Classification Method Using Packet Block Image." Electronics 12, no. 1 (December 27, 2022): 115. http://dx.doi.org/10.3390/electronics12010115.
Повний текст джерелаMegantara, Achmad, and Tohari Ahmad. "ANOVA-SVM for Selecting Subset Features in Encrypted Internet Traffic Classification." International Journal of Intelligent Engineering and Systems 14, no. 2 (April 30, 2021): 536–46. http://dx.doi.org/10.22266/ijies2021.0430.48.
Повний текст джерелаShapira, Tal, and Yuval Shavitt. "FlowPic: A Generic Representation for Encrypted Traffic Classification and Applications Identification." IEEE Transactions on Network and Service Management 18, no. 2 (June 2021): 1218–32. http://dx.doi.org/10.1109/tnsm.2021.3071441.
Повний текст джерела杨, 瑞鹏. "Encrypted Traffic Classification Based on Graph Embedding and Multimodal Deep Learning." Computer Science and Application 12, no. 05 (2022): 1425–35. http://dx.doi.org/10.12677/csa.2022.125142.
Повний текст джерелаMao, Jiaming, Mingming Zhang, Mu Chen, Lu Chen, Fei Xia, Lei Fan, ZiXuan Wang, and Wenbing Zhao. "Semisupervised Encrypted Traffic Identification Based on Auxiliary Classification Generative Adversarial Network." Computer Systems Science and Engineering 39, no. 3 (2021): 373–90. http://dx.doi.org/10.32604/csse.2021.018086.
Повний текст джерелаSheluhin, Oleg, Vyacheslav Barkov, and Mikhail Polkovnikov. "Classification of Encrypted Mobile App Traffic Using the Machine Learning Method." Voprosy kiberbezopasnosti, no. 4(28) (2018): 21–28. http://dx.doi.org/10.21681/2311-3456-2018-4-21-28.
Повний текст джерелаShen, Meng, Yiting Liu, Liehuang Zhu, Ke Xu, Xiaojiang Du, and Nadra Guizani. "Optimizing Feature Selection for Efficient Encrypted Traffic Classification: A Systematic Approach." IEEE Network 34, no. 4 (July 2020): 20–27. http://dx.doi.org/10.1109/mnet.011.1900366.
Повний текст джерелаIliyasu, Auwal Sani, and Huifang Deng. "Semi-Supervised Encrypted Traffic Classification With Deep Convolutional Generative Adversarial Networks." IEEE Access 8 (2020): 118–26. http://dx.doi.org/10.1109/access.2019.2962106.
Повний текст джерелаFu, Yanjie, Hui Xiong, Xinjiang Lu, Jin Yang, and Can Chen. "Service Usage Classification with Encrypted Internet Traffic in Mobile Messaging Apps." IEEE Transactions on Mobile Computing 15, no. 11 (November 1, 2016): 2851–64. http://dx.doi.org/10.1109/tmc.2016.2516020.
Повний текст джерелаOh, Chaeyeon, Joonseo Ha, and Heejun Roh. "A Survey on TLS-Encrypted Malware Network Traffic Analysis Applicable to Security Operations Centers." Applied Sciences 12, no. 1 (December 24, 2021): 155. http://dx.doi.org/10.3390/app12010155.
Повний текст джерелаHaoLi. "Traffic classification algorithm using CNN and multi-head attention mechanism for representation learning." Journal of Physics: Conference Series 2258, no. 1 (April 1, 2022): 012001. http://dx.doi.org/10.1088/1742-6596/2258/1/012001.
Повний текст джерела