{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T18:24:29Z","timestamp":1770229469031,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":20,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819698714","type":"print"},{"value":"9789819698721","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-96-9872-1_14","type":"book-chapter","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T14:34:40Z","timestamp":1753281280000},"page":"164-175","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Malicious Encrypted Traffic Detection with Transformer and Dual-Layer Meta-update Incremental Learning"],"prefix":"10.1007","author":[{"given":"Weiye","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haohan","family":"Tan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lixun","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenguang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinming","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"key":"14_CR1","doi-asserted-by":"crossref","unstructured":"Zhao, R., Deng, X., Yan, Z., et al.: Mt-flowformer: A semi-supervised flow transformer for encrypted traffic classification. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 2576\u20132584 (2022)","DOI":"10.1145\/3534678.3539314"},{"key":"14_CR2","doi-asserted-by":"crossref","unstructured":"Anderson, B., McGrew, D.: Identifying encrypted malware traffic with contextual flow data. In: Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security. pp. 35\u201346 (2016)","DOI":"10.1145\/2996758.2996768"},{"issue":"3","key":"14_CR3","doi-asserted-by":"publisher","first-page":"788","DOI":"10.1109\/TIFS.2017.2768018","volume":"13","author":"J Kohout","year":"2017","unstructured":"Kohout, J., Pevn\u00fd, T.: Network traffic fingerprinting based on approximated kernel two-sample test. IEEE Trans. Inf. Forensics Secur. 13(3), 788\u2013801 (2017)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"14_CR4","doi-asserted-by":"crossref","unstructured":"McGrew, D., Anderson, B.: Enhanced telemetry for encrypted threat analytics. In: 2016 IEEE 24th International Conference on Network Protocols (ICNP), pp. 1\u20136. IEEE (2016)","DOI":"10.1109\/ICNP.2016.7785325"},{"key":"14_CR5","doi-asserted-by":"crossref","unstructured":"Wang, W., Zhu, M., Zeng, X., et al.: Malware traffic classification using convolutional neural network for representation learning. In: 2017 International Conference on Information Networking (ICOIN), pp. 712\u2013717. IEEE (2017)","DOI":"10.1109\/ICOIN.2017.7899588"},{"key":"14_CR6","doi-asserted-by":"crossref","unstructured":"Anderson, B., McGrew, D.: Machine learning for encrypted malware traffic classification: accounting for noisy labels and non-stationarity. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. pp. 1723\u20131732 (2017)","DOI":"10.1145\/3097983.3098163"},{"key":"14_CR7","doi-asserted-by":"crossref","unstructured":"Lotfollahi, M., Jafari Siavoshani, M., Shirali Hossein Zade, R., et al.: Deep packet: a novel approach for encrypted traffic classification using deep learning. Soft Comput. 24(3), 1999\u20132012 (2020)","DOI":"10.1007\/s00500-019-04030-2"},{"issue":"13","key":"14_CR8","doi-asserted-by":"publisher","first-page":"3521","DOI":"10.1073\/pnas.1611835114","volume":"114","author":"J Kirkpatrick","year":"2017","unstructured":"Kirkpatrick, J., Pascanu, R., Rabinowitz, N., et al.: Overcoming catastrophic forgetting in neural networks. Proc. Natl. Acad. Sci. 114(13), 3521\u20133526 (2017)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"14_CR9","doi-asserted-by":"crossref","unstructured":"MontazeriShatoori, M., Davidson, L., Kaur, G., et al.: Detection of DOH tunnels using time-series classification of encrypted traffic. In: 2020 IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing, International Conference on Cyber Science and Technology Congress (DASC\/PiCom\/CBDCom\/CyberSciTech), pp. 63\u201370. IEEE (2020)","DOI":"10.1109\/DASC-PICom-CBDCom-CyberSciTech49142.2020.00026"},{"key":"14_CR10","doi-asserted-by":"crossref","unstructured":"Lashkari, A.H., Kadir, A.F.A., Taheri, L., et al.: Toward developing a systematic approach to generate benchmark android malware datasets and classification. In: 2018 International Carnahan Conference on Security technology (ICCST), pp. 1\u20137. IEEE (2018)","DOI":"10.1109\/CCST.2018.8585560"},{"key":"14_CR11","doi-asserted-by":"crossref","unstructured":"Liu, C., He, L., Xiong, G., et al.: FS-net: a flow sequence network for encrypted traffic classification. In: IEEE INFOCOM 2019-IEEE Conference on Computer Communications, pp. 1171\u20131179. IEEE (2019)","DOI":"10.1109\/INFOCOM.2019.8737507"},{"key":"14_CR12","doi-asserted-by":"crossref","unstructured":"Zhou, P., Liu, Y., Ma, L., et al.: Etguard: malicious encrypted traffic detection in blockchain-based power grid systems. arXiv preprint arXiv:2408.10657 (2024)","DOI":"10.1007\/978-981-97-9412-6_40"},{"key":"14_CR13","doi-asserted-by":"crossref","unstructured":"Taud, H., Mas, J.F.: Multilayer perceptron (MLP). Geomatic approaches for modeling land change scenarios, pp. 451\u2013455 (2018)","DOI":"10.1007\/978-3-319-60801-3_27"},{"key":"14_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-021-00444-8","volume":"8","author":"L Alzubaidi","year":"2021","unstructured":"Alzubaidi, L., Zhang, J., Humaidi, A.J., et al.: Review of deep learning: concepts, CNN architectures, challenges, applications, future directions. J. Big Data 8, 1\u201374 (2021)","journal-title":"J. Big Data"},{"key":"14_CR15","doi-asserted-by":"crossref","unstructured":"Cho, K., Van Merri\u00ebnboer, B., Gulcehre, C., et al.: Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078 (2014)","DOI":"10.3115\/v1\/D14-1179"},{"key":"14_CR16","doi-asserted-by":"crossref","unstructured":"Graves, A., Fern\u00e1ndez, S., Schmidhuber, J.: Bidirectional LSTM networks for improved phoneme classification and recognition. In: International Conference on Artificial Neural Networks,pp. 799\u2013804. Springer (2005)","DOI":"10.1007\/11550907_126"},{"key":"14_CR17","unstructured":"Mnih, V.: Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602 (2013)"},{"key":"14_CR18","first-page":"15920","volume":"33","author":"P Buzzega","year":"2020","unstructured":"Buzzega, P., Boschini, M., Porrello, A., et al.: Dark experience for general continual learning: a strong, simple baseline. Adv. Neural. Inf. Process. Syst. 33, 15920\u201315930 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"14_CR19","unstructured":"Riemer, M., Cases, I., Ajemian, R., et al.: Learning to learn without forgetting by maximizing transfer and minimizing interference. arXiv preprint arXiv:1810.11910 (2018)"},{"key":"14_CR20","unstructured":"Aljundi, R., Lin, M., Goujaud, B., et al.: Gradient based sample selection for online continual learning. Adv. Neural Inform. Process. Syst. 32 (2019)"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-9872-1_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T06:23:40Z","timestamp":1770186220000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-9872-1_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819698714","9789819698721"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-9872-1_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"24 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ningbo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}