{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T04:11:42Z","timestamp":1763007102010,"version":"3.45.0"},"publisher-location":"Singapore","reference-count":14,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819530540"},{"type":"electronic","value":"9789819530557"}],"license":[{"start":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T00:00:00Z","timestamp":1763078400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T00:00:00Z","timestamp":1763078400000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-3055-7_18","type":"book-chapter","created":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T04:07:29Z","timestamp":1763006849000},"page":"227-239","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["FATFI: A Framework to\u00a0Generate Adversarial Traffic with\u00a0Feature Interpretability"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-6322-5300","authenticated-orcid":false,"given":"Yikang","family":"Wang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3235-3463","authenticated-orcid":false,"given":"Weina","family":"Niu","sequence":"additional","affiliation":[]},{"given":"Dujuan","family":"Gu","sequence":"additional","affiliation":[]},{"given":"Qingjun","family":"Yuan","sequence":"additional","affiliation":[]},{"given":"Jiacheng","family":"Gong","sequence":"additional","affiliation":[]},{"given":"Shuangqi","family":"Gan","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Xiaosong","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,14]]},"reference":[{"issue":"10","key":"18_CR1","doi-asserted-by":"publisher","first-page":"4170","DOI":"10.3390\/app14104170","volume":"14","author":"O Arreche","year":"2024","unstructured":"Arreche, O., Guntur, T., Abdallah, M.: XAI-IDs: toward proposing an explainable artificial intelligence framework for enhancing network intrusion detection systems. Appl. Sci. 14(10), 4170 (2024)","journal-title":"Appl. Sci."},{"key":"18_CR2","doi-asserted-by":"crossref","unstructured":"Clements, J., Yang, Y., Sharma, A., Hu, H., Lao, Y.: Rallying adversarial techniques against deep learning for network security. In: Proceedings of the 2021 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 01\u201308. IEEE (2021)","DOI":"10.1109\/SSCI50451.2021.9660011"},{"key":"18_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2021.102367","volume":"109","author":"P Duy","year":"2021","unstructured":"Duy, P., Khoa, N., Nguyen, A., Pham, V.: Digfupas: deceive ids with GAN and function-preserving on adversarial samples in SDN-enabled networks. Comput. Secur. 109, 102367 (2021)","journal-title":"Comput. Secur."},{"key":"18_CR4","unstructured":"Hinton, G.: Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 (2015)"},{"key":"18_CR5","doi-asserted-by":"crossref","unstructured":"Lin, Z., Shi, Y., Xue, Z.: IDSGAN: generative adversarial networks for attack generation against intrusion detection. In: Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 79\u201391 (2022)","DOI":"10.1007\/978-3-031-05981-0_7"},{"issue":"2","key":"18_CR6","first-page":"43","volume":"12","author":"Z Liu","year":"2022","unstructured":"Liu, Z., Shi, Y.: A hybrid ids using GA-based feature selection method and random forest. Int. J. Mach. Learn. Comput. 12(2), 43\u201350 (2022)","journal-title":"Int. J. Mach. Learn. Comput."},{"key":"18_CR7","unstructured":"Lundberg, S.: A unified approach to interpreting model predictions. arXiv preprint arXiv:1705.07874 (2017)"},{"key":"18_CR8","doi-asserted-by":"crossref","unstructured":"Mirsky, Y., Doitshman, T., Elovici, Y., Shabtai, A.: Kitsune: an ensemble of autoencoders for online network intrusion detection. arXiv preprint arXiv:1802.09089 (2018)","DOI":"10.14722\/ndss.2018.23204"},{"key":"18_CR9","doi-asserted-by":"crossref","unstructured":"Ribeiro, M., Singh, S., Guestrin, C.: \u201cwhy should i trust you?\u201d Explaining the predictions of any classifier. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1135\u20131144 (2016)","DOI":"10.1145\/2939672.2939778"},{"key":"18_CR10","doi-asserted-by":"crossref","unstructured":"Sharafaldin, I., Lashkari, A., Ghorbani, A., et\u00a0al.: Toward generating a new intrusion detection dataset and intrusion traffic characterization. In: Proceedings of the International Conference on Information Systems Security and Privacy (ICISSP), pp. 108\u2013116 (2018)","DOI":"10.5220\/0006639801080116"},{"key":"18_CR11","doi-asserted-by":"publisher","first-page":"3225","DOI":"10.1109\/TIFS.2022.3201377","volume":"17","author":"Y Sharon","year":"2022","unstructured":"Sharon, Y., Berend, D., Liu, Y., Shabtai, A., Elovici, Y.: Tantra: timing-based adversarial network traffic reshaping attack. IEEE Trans. Inf. Forensics Secur. 17, 3225\u20133237 (2022)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"issue":"1","key":"18_CR12","doi-asserted-by":"publisher","first-page":"1249","DOI":"10.1007\/s12652-020-02167-9","volume":"12","author":"A Thakkar","year":"2021","unstructured":"Thakkar, A., Lohiya, R.: Attack classification using feature selection techniques: a comparative study. J. Ambient. Intell. Humaniz. Comput. 12(1), 1249\u20131266 (2021)","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"key":"18_CR13","unstructured":"Wright, C., Coull, S., Monrose, F.: Traffic morphing: an efficient defense against statistical traffic analysis. In: Proceedings of the 16th Annual Network and Distributed System Security Symposium (NDSS), p.\u00a09 (2009)"},{"key":"18_CR14","doi-asserted-by":"crossref","unstructured":"Yao, L., Niu, W., Yuan, Q., Li, B., Zhang, Y., Zhang, X.: A robust malicious traffic detection framework with low-quality labeled data. In: Proceedings of the IEEE International Conference on Communications (ICC 2024), pp. 2719\u20132724. IEEE (2024)","DOI":"10.1109\/ICC51166.2024.10623013"}],"container-title":["Lecture Notes in Computer Science","Knowledge Science, Engineering and Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-3055-7_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T04:07:31Z","timestamp":1763006851000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-3055-7_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,14]]},"ISBN":["9789819530540","9789819530557"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-3055-7_18","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025,11,14]]},"assertion":[{"value":"14 November 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"KSEM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Knowledge Science, Engineering and Management","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Macao","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":"4 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ksem2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ksem2025.scimeeting.cn\/en\/web\/index\/27434","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}