{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T15:22:31Z","timestamp":1759332151324,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031425189"},{"type":"electronic","value":"9783031425196"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-42519-6_13","type":"book-chapter","created":{"date-parts":[[2023,8,26]],"date-time":"2023-08-26T21:01:51Z","timestamp":1693083711000},"page":"132-143","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Phishing URL Detection with Prototypical Neural Network Disentangled by Triplet Sampling"],"prefix":"10.1007","author":[{"given":"Seok-Jun","family":"Bu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sung-Bae","family":"Cho","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,8,27]]},"reference":[{"key":"13_CR1","doi-asserted-by":"crossref","unstructured":"Purwanto, R.W., Pal, A., Blair, A., Jha, S.: PhishSim: aiding phishing website detection with a feature-free tool. IEEE Trans. Inf. Forensics Secur. 17, 1497\u20131512 (2022)","DOI":"10.1109\/TIFS.2022.3164212"},{"key":"13_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.116239","volume":"191","author":"CMR da Silva","year":"2022","unstructured":"da Silva, C.M.R., Fernandes, B.J.T., Feitosa, E.L., Garcia, V.C.: Piracema. io: A rules-based tree model for phishing prediction. Expert Syst. Appl. 191, 116239 (2022)","journal-title":"Expert Syst. Appl."},{"key":"13_CR3","doi-asserted-by":"crossref","unstructured":"Huang, L., Jia, S., Balcetis, E., Zhu, Q.: Advert: an adaptive and data-driven attention enhancement mechanism for phishing prevention. IEEE Trans. Inf. Forensics Secur. 17, 2585\u20132597 (2022)","DOI":"10.1109\/TIFS.2022.3189530"},{"key":"13_CR4","doi-asserted-by":"crossref","unstructured":"Anand, A., Gorde, K., Moniz, J.R.A., Park, N., Chakraborty, T., Chu, B.-T.: Phishing URL detection with oversampling based on text generative adversarial networks. In: IEEE International Conference on Big Data, pp. 1168\u20131177. IEEE (2018)","DOI":"10.1109\/BigData.2018.8622547"},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"Shirazi, H., Muramudalige, S.R., Ray, I., Jayasumana, A.P., Wang, H.: Adversarial autoencoder data synthesis for enhancing machine learning-based phishing detection algorithms. IEEE Trans. Serv. Comput. 16, 2411\u20132422 (2023)","DOI":"10.1109\/TSC.2023.3234806"},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Liu, C., et al.: Learning a few-shot embedding model with contrastive learning. In: Proceedings of the AAAI Conference on Artificial Intelligence, 2021, vol. 35, no. 10, pp. 8635\u20138643","DOI":"10.1609\/aaai.v35i10.17047"},{"key":"13_CR7","doi-asserted-by":"crossref","unstructured":"Sung, F., Yang, Y., Zhang, L., Xiang, T., Torr, P.H., Hospedales, T.M.: Learning to compare: relation network for few-shot learning. In: IEEE Conf. on Computer Vision and Pattern Recognition, pp. 1199\u20131208 (2018)","DOI":"10.1109\/CVPR.2018.00131"},{"key":"13_CR8","doi-asserted-by":"crossref","unstructured":"Jiang, W., Huang, K., Geng, J., Deng, X.: Multi-scale metric learning for few-shot learning. IEEE Trans. Circuits Syst. Video Technol. 31(3), 1091\u20131102 (2020)","DOI":"10.1109\/TCSVT.2020.2995754"},{"key":"13_CR9","unstructured":"Snell, J., Swersky, K., Zemel, R.: Prototypical networks for few-shot learning. Adv. in Neural Information Processing systems, vol. 30 (2017)"},{"key":"13_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2021.102273","volume":"106","author":"P Wang","year":"2021","unstructured":"Wang, P., Tang, Z., Wang, J.: A novel few-shot malware classification approach for unknown family recognition with multi-prototype modeling. Comput. Secur. 106, 102273 (2021)","journal-title":"Comput. Secur."},{"key":"13_CR11","doi-asserted-by":"crossref","unstructured":"Chai, Y., Du, L., Qiu, J., Yin, L., Tian, Z.: Dynamic prototype network based on sample adaptation for few-shot malware detection. IEEE Trans. Knowl. Data Eng. (2022)","DOI":"10.1109\/TKDE.2022.3142820"},{"key":"13_CR12","unstructured":"Le, H., Pham, Q., Sahoo, D., Hoi, S.C.: URLNet: learning a URL representation with deep learning for malicious URL detection, arXiv preprint arXiv:1802.03162 (2018)"},{"key":"13_CR13","doi-asserted-by":"crossref","unstructured":"Tajaddodianfar, F., Stokes, J.W., Gururajan, A.: Texception: a character\/word-level deep learning model for phishing URL detection. In: IEEE Int. Conf. on Acoustics, Speech and Signal Processing, pp. 2857\u20132861. IEEE (2020)","DOI":"10.1109\/ICASSP40776.2020.9053670"},{"key":"13_CR14","doi-asserted-by":"crossref","unstructured":"Chou, E.J., Gururajan, A., Laine, K., Goel, N.K., Bertiger, A., Stokes, J.W.: Privacy-preserving phishing web page classification via fully homomorphic encryption. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 2792\u20132796. IEEE (2020)","DOI":"10.1109\/ICASSP40776.2020.9053729"},{"issue":"12","key":"13_CR15","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.3390\/electronics10121492","volume":"10","author":"S-J Bu","year":"2021","unstructured":"Bu, S.-J., Cho, S.-B.: Deep character-level anomaly detection based on a convolutional autoencoder for zero-day phishing URL detection. Electronics 10(12), 1492 (2021)","journal-title":"Electronics"},{"issue":"01","key":"13_CR16","doi-asserted-by":"publisher","first-page":"3183","DOI":"10.1609\/aaai.v33i01.33013183","volume":"33","author":"C Arachie","year":"2019","unstructured":"Arachie, C., Huang, B.: Adversarial label learning. AAAI Conf. on Artificial Intelligence 33(01), 3183\u20133190 (2019)","journal-title":"AAAI Conf. on Artificial Intelligence"},{"key":"13_CR17","doi-asserted-by":"publisher","unstructured":"Park, K.-W., Bu, S.-J., Cho, S.-B.: Evolutionary optimization of neuro-symbolic integration for phishing URL detection. In: International Conference on Hybrid Artificial Intelligence Systems, pp. 88\u2013100. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86271-8_8","DOI":"10.1007\/978-3-030-86271-8_8"},{"key":"13_CR18","doi-asserted-by":"crossref","unstructured":"Bu, S.-J., Cho, S.-B.: Integrating deep learning with first-order logic programmed constraints for zero-day phishing attack detection. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 2685\u20132689. IEEE (2021)","DOI":"10.1109\/ICASSP39728.2021.9414850"}],"container-title":["Lecture Notes in Networks and Systems","International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023)"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-42519-6_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,26]],"date-time":"2023-08-26T21:03:03Z","timestamp":1693083783000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-42519-6_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031425189","9783031425196"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-42519-6_13","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"27 August 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CISIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Computational Intelligence in Security for Information Systems Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Salamanca","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cisis-spain2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2023.cisisconference.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}