{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T16:47:16Z","timestamp":1762015636455,"version":"3.40.3"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030295509"},{"type":"electronic","value":"9783030295516"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-29551-6_41","type":"book-chapter","created":{"date-parts":[[2019,8,20]],"date-time":"2019-08-20T12:04:02Z","timestamp":1566302642000},"page":"464-471","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["D3N: DGA Detection with Deep-Learning Through NXDomain"],"prefix":"10.1007","author":[{"given":"Mingkai","family":"Tong","sequence":"first","affiliation":[]},{"given":"Xiaoqing","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Jiahai","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Hui","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Shuang","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Xinran","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Heng","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,8,21]]},"reference":[{"key":"41_CR1","unstructured":"Alexa.com: Alexa Top 500 Global Sites (2019). \nhttps:\/\/www.alexa.com\/topsites"},{"key":"41_CR2","doi-asserted-by":"crossref","unstructured":"Anderson, H.S., Woodbridge, J., Filar, B.: DeepDGA: adversarially-tuned domain generation and detection. In: Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security, pp. 13\u201321. ACM (2016)","DOI":"10.1145\/2996758.2996767"},{"key":"41_CR3","unstructured":"Antonakakis, M., Perdisci, R., Dagon, D., Lee, W., Feamster, N.: Building a dynamic reputation system for DNS. In: USENIX Security Symposium, pp. 273\u2013290 (2010)"},{"key":"41_CR4","unstructured":"Antonakakis, M., et al.: From throw-away traffic to bots: detecting the rise of DGA-based malware. In: Presented as Part of the 21st $$\\{$$USENIX$$\\}$$ Security Symposium ($$\\{$$USENIX$$\\}$$ Security 12), pp. 491\u2013506 (2012)"},{"key":"41_CR5","doi-asserted-by":"crossref","unstructured":"Khalil, I., Yu, T., Guan, B.: Discovering malicious domains through passive DNS data graph analysis. In: Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security, pp. 663\u2013674. ACM (2016)","DOI":"10.1145\/2897845.2897877"},{"key":"41_CR6","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.comcom.2014.04.013","volume":"49","author":"J Lee","year":"2014","unstructured":"Lee, J., Lee, H.: GMAD: graph-based malware activity detection by DNS traffic analysis. Comput. Commun. 49, 33\u201347 (2014)","journal-title":"Comput. Commun."},{"key":"41_CR7","doi-asserted-by":"publisher","unstructured":"Lin Jin, H.S.: CDN list [Data set] (2019). \nhttps:\/\/doi.org\/10.5281\/zenodo.842988","DOI":"10.5281\/zenodo.842988"},{"key":"41_CR8","unstructured":"Lison, P., Mavroeidis, V.: Automatic detection of malware-generated domains with recurrent neural models. arXiv preprint \narXiv:1709.07102\n\n (2017)"},{"key":"41_CR9","unstructured":"Netgate.com: Services DNS Configuring Dynamic DNS pfSense Documentation (2019). \nhttps:\/\/www.netgate.com\/docs\/pfsense\/dns\/dynamic-dns.html"},{"key":"41_CR10","unstructured":"Passivedns.cn: Sign In-passiveDNS (2019). \nhttp:\/\/netlab.360.com\/"},{"key":"41_CR11","unstructured":"Plohmann, D., Yakdan, K., Klatt, M., Bader, J., Gerhards-Padilla, E.: A comprehensive measurement study of domain generating malware. In: 25th $$\\{$$USENIX$$\\}$$ Security Symposium ($$\\{$$USENIX$$\\}$$ Security 16), pp. 263\u2013278 (2016)"},{"key":"41_CR12","unstructured":"Publicsuffix.org: Public suffix list. \nhttps:\/\/publicsuffix.org\/\n\n. Accessed 7 Jun 2019"},{"key":"41_CR13","unstructured":"Sch\u00fcppen, S., Teubert, D., Herrmann, P., Meyer, U.: $$\\{$$FANCI$$\\}$$: feature-based automated NXdomain classification and intelligence. In: 27th $$\\{$$USENIX$$\\}$$ Security Symposium ($$\\{$$USENIX$$\\}$$ Security 18), pp. 1165\u20131181 (2018)"},{"key":"41_CR14","unstructured":"Woodbridge, J., Anderson, H.S., Ahuja, A., Grant, D.: Predicting domain generation algorithms with long short-term memory networks. arXiv preprint \narXiv:1611.00791\n\n (2016)"}],"container-title":["Lecture Notes in Computer Science","Knowledge Science, Engineering and Management"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-29551-6_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,2,22]],"date-time":"2020-02-22T09:06:56Z","timestamp":1582362416000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-29551-6_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030295509","9783030295516"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-29551-6_41","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"21 August 2019","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":"Athens","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 August 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ksem2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ksem.conferences.academy\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"240","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"77","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"26","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"32% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}