{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T03:06:17Z","timestamp":1784430377998,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":93,"publisher":"ACM","funder":[{"name":"National Nature Science Foundation of China","award":["No.62072446, No.62072431, No.62102430, No.62201600, No.62472247 and No.62306179"],"award-info":[{"award-number":["No.62072446, No.62072431, No.62102430, No.62201600, No.62472247 and No.62306179"]}]},{"name":"NUDT Grants","award":["No.ZK22-50, No.ZK22-56"],"award-info":[{"award-number":["No.ZK22-50, No.ZK22-56"]}]},{"name":"Other Program","award":["24BC3200100"],"award-info":[{"award-number":["24BC3200100"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,19]]},"DOI":"10.1145\/3719027.3744804","type":"proceedings-article","created":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T23:32:38Z","timestamp":1763854358000},"page":"1664-1678","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["MM4flow: A Pre-trained Multi-modal Model for Versatile Network Traffic Analysis"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9306-2056","authenticated-orcid":false,"given":"Luming","family":"Yang","sequence":"first","affiliation":[{"name":"National University of Defense Technology, Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5930-8881","authenticated-orcid":false,"given":"Lin","family":"Liu","sequence":"additional","affiliation":[{"name":"National University of Defense Technology, Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2986-4665","authenticated-orcid":false,"given":"JunJie","family":"Huang","sequence":"additional","affiliation":[{"name":"National University of Defense Technology, Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7532-0434","authenticated-orcid":false,"given":"Zhuotao","family":"Liu","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2917-2033","authenticated-orcid":false,"given":"Shiyu","family":"Liang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7275-8190","authenticated-orcid":false,"given":"Shaojing","family":"Fu","sequence":"additional","affiliation":[{"name":"National University of Defense Technology, Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1796-5576","authenticated-orcid":false,"given":"Yongjun","family":"Wang","sequence":"additional","affiliation":[{"name":"National University of Defense Technology, Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,11,22]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICC42927.2021.9500316"},{"key":"e_1_3_2_1_2_1","first-page":"1","article-title":"Mobile encrypted traffic classification using deep learning. In 2018 Network traffic measurement and analysis conference (TMA)","author":"Aceto Giuseppe","year":"2018","unstructured":"Giuseppe Aceto, Domenico Ciuonzo, Antonio Montieri, and Antonio Pescap\u00e9. 2018. Mobile encrypted traffic classification using deep learning. In 2018 Network traffic measurement and analysis conference (TMA). IEEE, 1-8.","journal-title":"IEEE"},{"key":"e_1_3_2_1_3_1","volume-title":"MIMETIC: Mobile encrypted traffic classification using multimodal deep learning. Computer networks","author":"Aceto Giuseppe","year":"2019","unstructured":"Giuseppe Aceto, Domenico Ciuonzo, Antonio Montieri, and Antonio Pescap\u00e8. 2019a. MIMETIC: Mobile encrypted traffic classification using multimodal deep learning. Computer networks, Vol. 165 (2019), 106944."},{"key":"e_1_3_2_1_4_1","volume-title":"Mobile encrypted traffic classification using deep learning: Experimental evaluation, lessons learned, and challenges","author":"Aceto Giuseppe","year":"2019","unstructured":"Giuseppe Aceto, Domenico Ciuonzo, Antonio Montieri, and Antonio Pescap\u00e9. 2019b. Mobile encrypted traffic classification using deep learning: Experimental evaluation, lessons learned, and challenges. IEEE transactions on network and service management, Vol. 16, 2 (2019), 445-458."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2991079.2991123"},{"key":"e_1_3_2_1_6_1","unstructured":"Shane Alcock and Richard Nelson. 2012. Libprotoident: traffic classification using lightweight packet inspection. Technical Report. Technical report University of Waikato."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2996758.2996768"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11416-017-0306-6"},{"key":"e_1_3_2_1_9_1","volume-title":"FlowLens: Enabling Efficient Flow Classification for ML-based Network Security Applications. In Network and Distributed System Security Symposium.","author":"Barradas Diogo","year":"2021","unstructured":"Diogo Barradas, Nuno Santos, Lu\u00eds Rodrigues, Salvatore Signorello, Fernando M. V. Ramos, and Andr\u00e9 Madeira. 2021. FlowLens: Enabling Efficient Flow Classification for ML-based Network Security Applications. In Network and Distributed System Security Symposium."},{"key":"e_1_3_2_1_10_1","volume-title":"Proc. 7th USENIX security symposium.","author":"Bro Paxson V","year":"1998","unstructured":"Paxson V Bro. 1998. A system for detecting network intruders in real-time. In Proc. 7th USENIX security symposium."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2014.11.001"},{"key":"e_1_3_2_1_12_1","volume-title":"Rubi: Reducing unimodal biases for visual question answering. Advances in neural information processing systems","author":"Cadene Remi","year":"2019","unstructured":"Remi Cadene, Corentin Dancette, Matthieu Cord, Devi Parikh, et al., 2019. Rubi: Reducing unimodal biases for visual question answering. Advances in neural information processing systems, Vol. 32 (2019)."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58539-6_34"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSN50589.2020.00089"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2023.3322861"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcan.2021.09.009"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/PST55820.2022.9851966"},{"key":"e_1_3_2_1_18_1","unstructured":"DataCon-Community. 2020. DataCon2020 - Encrypted Malicious Traffic Dataset. https:\/\/datacon.qianxin.com\/opendata\/openpage?resourcesId=6."},{"key":"e_1_3_2_1_19_1","unstructured":"DataCon-Community. 2021. DataCon2021 - Encrypted Proxy Traffic Dataset. https:\/\/datacon.qianxin.com\/opendata\/openpage?resourcesId=10."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/IWCMC.2014.6906427"},{"key":"e_1_3_2_1_21_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.5220\/0005740704070414"},{"key":"e_1_3_2_1_23_1","volume-title":"International Conference on Machine Learning. PMLR, 8632-8656","author":"Du Chenzhuang","year":"2023","unstructured":"Chenzhuang Du, Jiaye Teng, Tingle Li, Yichen Liu, Tianyuan Yuan, Yue Wang, Yang Yuan, and Hang Zhao. 2023. On uni-modal feature learning in supervised multi-modal learning. In International Conference on Machine Learning. PMLR, 8632-8656."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2016.2551203"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3545948.3545983"},{"key":"e_1_3_2_1_26_1","first-page":"21630","volume-title":"Advances in Neural Information Processing Systems","volume":"34","author":"Gat Itai","year":"2021","unstructured":"Itai Gat, Idan Schwartz, and Alex Schwing. 2021. Perceptual Score: What Data Modalities Does Your Model Perceive?. In Advances in Neural Information Processing Systems, Vol. 34. Curran Associates, Inc., 21630-21643."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3607199.3607206"},{"key":"e_1_3_2_1_28_1","first-page":"1187","volume-title":"25th USENIX Security Symposium (USENIX Security 16)","author":"Hayes Jamie","year":"2016","unstructured":"Jamie Hayes and George Danezis. 2016. k-fingerprinting: A robust scalable website fingerprinting technique. In 25th USENIX Security Symposium (USENIX Security 16). 1187-1203."},{"key":"e_1_3_2_1_29_1","volume-title":"Zhi Guo Yang, and Xiang Ning Chen","author":"He Hong Ye","year":"2020","unstructured":"Hong Ye He, Zhi Guo Yang, and Xiang Ning Chen. 2020. PERT: Payload encoding representation from transformer for encrypted traffic classification. In 2020 ITU Kaleidoscope: Industry-Driven Digital Transformation (ITU K). IEEE, 1-8."},{"key":"e_1_3_2_1_30_1","first-page":"10944","article-title":"What makes multi-modal learning better than single (provably)","volume":"34","author":"Huang Yu","year":"2021","unstructured":"Yu Huang, Chenzhuang Du, Zihui Xue, Xuanyao Chen, Hang Zhao, and Longbo Huang. 2021. What makes multi-modal learning better than single (provably). Advances in Neural Information Processing Systems, Vol. 34 (2021), 10944-10956.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_31_1","volume-title":"International conference on machine learning. PMLR, 9226-9259","author":"Huang Yu","year":"2022","unstructured":"Yu Huang, Junyang Lin, Chang Zhou, Hongxia Yang, and Longbo Huang. 2022. Modality competition: What makes joint training of multi-modal network fail in deep learning?(provably). In International conference on machine learning. PMLR, 9226-9259."},{"key":"e_1_3_2_1_32_1","unstructured":"Internet Assigned Numbers Authority (IANA). 2024. Service name and transport protocol port number registry. [Online]. https:\/\/www.iana.org\/assignments\/service-names-port-numbers\/service-names-port-numbers.xhtml"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2022.109309"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.4304\/jnw.8.1.71-81"},{"key":"e_1_3_2_1_35_1","first-page":"781","volume-title":"IEEE INFOCOM 2014 - IEEE Conference on Computer Communications","author":"Duda Andrzej","year":"2014","unstructured":"Andrzej Duda. 2014. Markov chain fingerprinting to classify encrypted traffic. IEEE INFOCOM 2014 - IEEE Conference on Computer Communications (2014), 781-789."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.5220\/0006105602530262"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/CCST.2018.8585560"},{"key":"e_1_3_2_1_38_1","first-page":"1579","volume-title":"31st USENIX Security Symposium (USENIX Security 22)","author":"Li Jianfeng","year":"2022","unstructured":"Jianfeng Li, Hao Zhou, Shuohan Wu, Xiapu Luo, Ting Wang, Xian Zhan, and Xiaobo Ma. 2022. &#123;FOAP&#125;:&#123;Fine-Grained&#125;&#123;Open-World&#125; android app fingerprinting. In 31st USENIX Security Symposium (USENIX Security 22). 1579-1596."},{"key":"e_1_3_2_1_39_1","volume-title":"A closer look at the robustness of vision-and-language pre-trained models. arXiv preprint arXiv:2012.08673","author":"Li Linjie","year":"2020","unstructured":"Linjie Li, Zhe Gan, and Jingjing Liu. 2020. A closer look at the robustness of vision-and-language pre-trained models. arXiv preprint arXiv:2012.08673 (2020)."},{"key":"e_1_3_2_1_40_1","first-page":"1","volume-title":"Byte Segment Neural Network for Network Traffic Classification. 2018 IEEE\/ACM 26th International Symposium on Quality of Service (IWQoS)","author":"Li Rui","year":"2018","unstructured":"Rui Li, Xi Xiao, Shiguang Ni, Haitao Zheng, and Shutao Xia. 2018. Byte Segment Neural Network for Network Traffic Classification. 2018 IEEE\/ACM 26th International Symposium on Quality of Service (IWQoS) (2018), 1-10."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2021.107974"},{"key":"e_1_3_2_1_42_1","unstructured":"Xinjie Lin Gang Xiong Gaopeng Gou Zhen Li Junzheng Shi and J. Yu. 2022a. CSTNET-TLS 1.3 dataset. https:\/\/drive.google.com\/drive\/folders\/1BUo5TMRuXNvTqNYy0RLeHk4l4Q3BuzSk."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512217"},{"key":"e_1_3_2_1_44_1","first-page":"1","volume-title":"MaMPF: Encrypted Traffic Classification Based on Multi-Attribute Markov Probability Fingerprints. 2018 IEEE\/ACM 26th International Symposium on Quality of Service (IWQoS)","author":"Liu Chang","year":"2018","unstructured":"Chang Liu, Zigang Cao, Gang Xiong, Gaopeng Gou, Siu-Ming Yiu, and Longtao He. 2018. MaMPF: Encrypted Traffic Classification Based on Multi-Attribute Markov Probability Fingerprints. 2018 IEEE\/ACM 26th International Symposium on Quality of Service (IWQoS) (2018), 1-10."},{"key":"e_1_3_2_1_45_1","first-page":"1171","volume-title":"FS-Net: A Flow Sequence Network For Encrypted Traffic Classification. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications","author":"Liu Chang","year":"2019","unstructured":"Chang Liu, Longtao He, Gang Xiong, Zigang Cao, and Zhen Li. 2019. FS-Net: A Flow Sequence Network For Encrypted Traffic Classification. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications (2019), 1171-1179."},{"key":"e_1_3_2_1_46_1","volume-title":"Decoupled weight decay regularization. arXiv preprint arXiv:1711.05101","author":"Loshchilov I","year":"2017","unstructured":"I Loshchilov. 2017. Decoupled weight decay regularization. arXiv preprint arXiv:1711.05101 (2017)."},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-019-04030-2"},{"key":"e_1_3_2_1_48_1","first-page":"1","volume-title":"Byte-Label Joint Attention Learning for Packet-grained Network Traffic Classification. 2021 IEEE\/ACM 29th International Symposium on Quality of Service (IWQOS)","author":"Mao Kelong","year":"2021","unstructured":"Kelong Mao, Xi Xiao, Guangwu Hu, Xiapu Luo, Bin Zhang, and Shutao Xia. 2021. Byte-Label Joint Attention Learning for Packet-grained Network Traffic Classification. 2021 IEEE\/ACM 29th International Symposium on Quality of Service (IWQOS) (2021), 1-10."},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.5555\/1052084.1648647"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/1064212.1064220"},{"key":"e_1_3_2_1_51_1","volume-title":"WENC: HTTPS Encrypted Traffic Classification Using Weighted Ensemble Learning and Markov Chain. 2017 IEEE Trustcom\/BigDataSE\/ICESS","author":"Pan Wubin","year":"2017","unstructured":"Wubin Pan, Guang Cheng, and Yongning Tang. 2017. WENC: HTTPS Encrypted Traffic Classification Using Weighted Ensemble Learning and Markov Chain. 2017 IEEE Trustcom\/BigDataSE\/ICESS (2017), 50-57."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"crossref","unstructured":"Andriy Panchenko Fabian Lanze Jan Pennekamp Thomas Engel Andreas Zinnen Martin Henze and Klaus Wehrle. 2016. Website Fingerprinting at Internet Scale.. In NDSS.","DOI":"10.14722\/ndss.2016.23477"},{"key":"e_1_3_2_1_53_1","volume-title":"Bro: a system for detecting network intruders in real-time. Computer networks","author":"Paxson Vern","year":"1999","unstructured":"Vern Paxson. 1999. Bro: a system for detecting network intruders in real-time. Computer networks, Vol. 31, 23-24 (1999), 2435-2463."},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485832.3485925"},{"key":"e_1_3_2_1_55_1","unstructured":"Alec Radford. 2018. Improving language understanding by generative pre-training. (2018)."},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/SPW53761.2021.00014"},{"key":"e_1_3_2_1_57_1","volume-title":"Tom Van Goethem, and Wouter Joosen","author":"Rimmer Vera","year":"2017","unstructured":"Vera Rimmer, Davy Preuveneers, Marc Juarez, Tom Van Goethem, and Wouter Joosen. 2017. Automated website fingerprinting through deep learning. arXiv preprint arXiv:1708.06376 (2017)."},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOMW.2019.8845315"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2021.3071441"},{"key":"e_1_3_2_1_60_1","first-page":"108","article-title":"Toward generating a new intrusion detection dataset and intrusion traffic characterization","volume":"1","author":"Sharafaldin Iman","year":"2018","unstructured":"Iman Sharafaldin, Arash Habibi Lashkari, Ali A Ghorbani, et al., 2018. Toward generating a new intrusion detection dataset and intrusion traffic characterization. ICISSp, Vol. 1 (2018), 108-116.","journal-title":"ICISSp"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2019.8761167"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.3046876"},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2017.2692682"},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1109\/IWQoS.2016.7590451"},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2022.3208196"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2021.3050608"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3243768"},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2016.40"},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2017.2737970"},{"key":"e_1_3_2_1_70_1","volume-title":"Maarten Van Steen, and Andreas Peter","author":"Ede Thijs Van","year":"2020","unstructured":"Thijs Van Ede, Riccardo Bortolameotti, Andrea Continella, Jingjing Ren, Daniel J Dubois, Martina Lindorfer, David Choffnes, Maarten Van Steen, and Andreas Peter. 2020b. Browser dataset. https:\/\/drive.google.com\/open?id=1wOdrfazbrcMDrL0NfA4GLoWegtPqkPj3."},{"key":"e_1_3_2_1_71_1","volume-title":"Maarten Van Steen, and Andreas Peter","author":"Ede Thijs Van","year":"2020","unstructured":"Thijs Van Ede, Riccardo Bortolameotti, Andrea Continella, Jingjing Ren, Daniel J Dubois, Martina Lindorfer, David Choffnes, Maarten Van Steen, and Andreas Peter. 2020a. Flowprint: Semi-supervised mobile-app fingerprinting on encrypted network traffic. In Network and distributed system security symposium (NDSS), Vol. 27."},{"key":"e_1_3_2_1_72_1","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390294"},{"key":"e_1_3_2_1_73_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICNP61940.2024.10858569"},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01271"},{"key":"e_1_3_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISI.2017.8004872"},{"key":"e_1_3_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICOIN.2017.7899588"},{"key":"e_1_3_2_1_77_1","volume-title":"International Conference on Machine Learning. PMLR, 24043-24055","author":"Wu Nan","year":"2022","unstructured":"Nan Wu, Stanislaw Jastrzebski, Kyunghyun Cho, and Krzysztof J Geras. 2022. Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks. In International Conference on Machine Learning. PMLR, 24043-24055."},{"key":"e_1_3_2_1_78_1","volume-title":"RBLJAN: Robust Byte-Label Joint Attention Network for Network Traffic Classification","author":"Xiao Xi","year":"2024","unstructured":"Xi Xiao, Shuo Wang, Guangwu Hu, Qing Li, Kelong Mao, Xiapu Luo, Bin Zhang, and Shutao Xia. 2024. RBLJAN: Robust Byte-Label Joint Attention Network for Network Traffic Classification. IEEE Transactions on Dependable and Secure Computing (2024)."},{"key":"e_1_3_2_1_79_1","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2021.3101311"},{"key":"e_1_3_2_1_80_1","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2021.3101311"},{"key":"e_1_3_2_1_81_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3179955"},{"key":"e_1_3_2_1_82_1","doi-asserted-by":"publisher","DOI":"10.1109\/IWQoS61813.2024.10682894"},{"key":"e_1_3_2_1_83_1","unstructured":"LQ Zeek. 2024. The zeek network security monitor. https:\/\/zeek.org."},{"key":"e_1_3_2_1_84_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583227"},{"key":"e_1_3_2_1_85_1","first-page":"397","volume-title":"Autonomous Unknown-Application Filtering and Labeling for DL-based Traffic Classifier Update. IEEE INFOCOM 2020 - IEEE Conference on Computer Communications","author":"Zhang Jielun","year":"2020","unstructured":"Jielun Zhang, Fuhao Li, Feng Ye, and Hongyu Wu. 2020. Autonomous Unknown-Application Filtering and Labeling for DL-based Traffic Classifier Update. IEEE INFOCOM 2020 - IEEE Conference on Computer Communications (2020), 397-405."},{"key":"e_1_3_2_1_86_1","first-page":"59100","volume-title":"Proceedings of the 41st International Conference on Machine Learning","volume":"235","author":"Zhang Yedi","year":"2024","unstructured":"Yedi Zhang, Peter E. Latham, and Andrew M Saxe. 2024. Understanding Unimodal Bias in Multimodal Deep Linear Networks. In Proceedings of the 41st International Conference on Machine Learning, Vol. 235. PMLR, 59100-59125."},{"key":"e_1_3_2_1_87_1","doi-asserted-by":"publisher","DOI":"10.1109\/IWQoS54832.2022.9812882"},{"key":"e_1_3_2_1_88_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539314"},{"key":"e_1_3_2_1_89_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i4.25674"},{"key":"e_1_3_2_1_90_1","doi-asserted-by":"publisher","DOI":"10.1093\/comjnl\/bxad076"},{"key":"e_1_3_2_1_91_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380090"},{"key":"e_1_3_2_1_92_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-021-03032-8"},{"key":"e_1_3_2_1_93_1","volume-title":"TrafficFormer: An Efficient Pre-trained Model for Traffic Data. In IEEE Symposium on Security and Privacy. IEEE, 1-15","author":"Zhou Guangmeng","year":"2025","unstructured":"Guangmeng Zhou, Xiongwen Guo, Zhuotao Liu, Tong Li, Qi Li, and Ke Xu. 2025. TrafficFormer: An Efficient Pre-trained Model for Traffic Data. In IEEE Symposium on Security and Privacy. IEEE, 1-15."}],"event":{"name":"CCS '25: ACM SIGSAC Conference on Computer and Communications Security","location":"Taipei Taiwan","acronym":"CCS '25","sponsor":["SIGSAC ACM Special Interest Group on Security, Audit, and Control"]},"container-title":["Proceedings of the 2025 ACM SIGSAC Conference on Computer and Communications Security"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3719027.3744804","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T22:07:46Z","timestamp":1766441266000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3719027.3744804"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,19]]},"references-count":93,"alternative-id":["10.1145\/3719027.3744804","10.1145\/3719027"],"URL":"https:\/\/doi.org\/10.1145\/3719027.3744804","relation":{},"subject":[],"published":{"date-parts":[[2025,11,19]]},"assertion":[{"value":"2025-11-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}