{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T00:20:57Z","timestamp":1775694057443,"version":"3.50.1"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032169945","type":"print"},{"value":"9783032169952","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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\/978-3-032-16995-2_39","type":"book-chapter","created":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T23:42:09Z","timestamp":1775691729000},"page":"435-446","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Generation of\u00a0Semantic Explanations for\u00a0AI-Based Models for\u00a0Network Intrusion Detection"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-1607-2541","authenticated-orcid":false,"given":"Enrique","family":"Fern\u00e1ndez-Morales","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2779-4042","authenticated-orcid":false,"given":"Llanos","family":"Tobarra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5181-0199","authenticated-orcid":false,"given":"Antonio","family":"Robles-G\u00f3mez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4089-9538","authenticated-orcid":false,"given":"Rafael","family":"Pastor-Vargas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3707-7582","authenticated-orcid":false,"given":"Pedro","family":"Vidal-Balboa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,4,1]]},"reference":[{"key":"39_CR1","unstructured":"ISO\/IEC 23894:2023 - information technology \u2014 artificial intelligence \u2014 guidance on risk management (2023). https:\/\/www.iso.org\/standard\/77304.html"},{"key":"39_CR2","doi-asserted-by":"publisher","unstructured":"Adadi, A., Berrada, M.: Peeking inside the black-box: a survey on explainable artificial intelligence (XAI). IEEE Access PP, 1\u20131 (2018). https:\/\/doi.org\/10.1109\/ACCESS.2018.2870052","DOI":"10.1109\/ACCESS.2018.2870052"},{"issue":"10","key":"39_CR3","doi-asserted-by":"publisher","first-page":"8357","DOI":"10.1109\/JIOT.2023.3234530","volume":"10","author":"P Bhale","year":"2023","unstructured":"Bhale, P., Chowdhury, D.R., Biswas, S., Nandi, S.: Optimist: lightweight and transparent ids with optimum placement strategy to mitigate mixed-rate ddos attacks in iot networks. IEEE Internet Things J. 10(10), 8357\u20138370 (2023). https:\/\/doi.org\/10.1109\/JIOT.2023.3234530","journal-title":"IEEE Internet Things J."},{"key":"39_CR4","doi-asserted-by":"publisher","first-page":"4851","DOI":"10.1109\/TIFS.2024.3385321","volume":"19","author":"G Duan","year":"2024","unstructured":"Duan, G., Lv, H., Wang, H., Feng, G., Li, X.: Practical cyber attack detection with continuous temporal graph in dynamic network system. IEEE Trans. Inf. Forensics Secur. 19, 4851\u20134864 (2024). https:\/\/doi.org\/10.1109\/TIFS.2024.3385321","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"39_CR5","unstructured":"European Commission: Artificial Intelligence Act. Regulation (EU) 2024\/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence and amending Regulations (EC) No 300\/2008, (EU) No 167\/2013, (EU) No 168\/2013, (EU) 2018\/858, (EU) 2018\/1139 and (EU) 2019\/2144 and Directives 2014\/90\/EU, (EU) 2016\/797 and (EU) 2020\/1828 (Artificial Intelligence Act) (2024), https:\/\/eur-lex.europa.eu\/eli\/reg\/2024\/1689\/oj\/eng"},{"key":"39_CR6","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez-Morales, E., Tobarra, L., Robles-G\u00f3mez, A., Pastor-Vargas, R., Vidal-Balboa, P., Sarraipa, J.: Anomaly detection in smart rural IoT systems. In: DCAI 2025. Lecture Notes in Networks and Systems, Springer (2025)","DOI":"10.1007\/978-3-032-04160-9_7"},{"issue":"5","key":"39_CR7","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1214\/aos\/1013203451","volume":"29","author":"JH Friedman","year":"2001","unstructured":"Friedman, J.H.: Greedy function approximation: a gradient boosting machine. Ann. Stat. 29(5), 1189\u20131232 (2001). https:\/\/doi.org\/10.1214\/aos\/1013203451","journal-title":"Ann. Stat."},{"key":"39_CR8","doi-asserted-by":"publisher","first-page":"30164","DOI":"10.1109\/ACCESS.2024.3368377","volume":"12","author":"D Gaspar","year":"2024","unstructured":"Gaspar, D., Silva, P., Silva, C.: Explainable ai for intrusion detection systems: lime and shap applicability on multi-layer perceptron. IEEE Access 12, 30164\u201330175 (2024). https:\/\/doi.org\/10.1109\/ACCESS.2024.3368377","journal-title":"IEEE Access"},{"issue":"1","key":"39_CR9","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1080\/10618600.2014.907095","volume":"24","author":"A Goldstein","year":"2015","unstructured":"Goldstein, A., Kapelner, A., Bleich, J., Pitkin, E.: Peeking inside the black box: visualizing statistical learning with plots of individual conditional expectation. J. Comput. Graph. Stat. 24(1), 44\u201365 (2015). https:\/\/doi.org\/10.1080\/10618600.2014.907095","journal-title":"J. Comput. Graph. Stat."},{"key":"39_CR10","unstructured":"Klaise, J., Looveren, A.V., Vacanti, G., Coca, A.: Alibi explain: algorithms for explaining machine learning models. J. Mach. Learn. Res. 22(181), 1\u20137 (2021). http:\/\/jmlr.org\/papers\/v22\/21-0017.html"},{"key":"39_CR11","unstructured":"Lundberg, S.M., Lee, S.I.: A unified approach to interpreting model predictions. In: Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. (eds.) Advances in Neural Information Processing Systems 30, pp. 4765\u20134774. Curran Associates, Inc. (2017). http:\/\/papers.nips.cc\/paper\/7062-a-unified-approach-to-interpreting-model-predictions.pdf"},{"key":"39_CR12","unstructured":"Microsoft: The stride threat model (2009). https:\/\/learn.microsoft.com\/en-us\/previous-versions\/commerce-server\/ee823878(v=cs.20)?redirectedfrom=MSDN"},{"key":"39_CR13","unstructured":"Mitchell, T.M.: Machine Learning. McGraw-Hill Series in Computer Science (1997)"},{"key":"39_CR14","doi-asserted-by":"publisher","first-page":"1775","DOI":"10.1109\/COMST.2023.3280465","volume":"25","author":"N Moustafa","year":"2023","unstructured":"Moustafa, N., Koroniotis, N., Keshk, M., Zomaya, A.Y., Tari, Z.: Explainable intrusion detection for cyber defences in the internet of things: opportunities and solutions. IEEE Commun. Surv. Tutor. 25, 1775\u20131807 (2023). https:\/\/doi.org\/10.1109\/COMST.2023.3280465","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"39_CR15","unstructured":"Mundhenk, T.N., Chen, B.Y., Friedland, G.: Efficient saliency maps for explainable AI. CoRR abs\/1911.11293 (2019). http:\/\/arxiv.org\/abs\/1911.11293"},{"key":"39_CR16","unstructured":"National Institute of Standards and Technology (NIST): AI Risk Management Framework: Second Draft (AI RMF 2.0) (2022). https:\/\/www.nist.gov\/system\/files\/documents\/2022\/08\/18\/AI_RMF_2nd_draft.pdf, framework for managing risks associated with AI systems"},{"key":"39_CR17","unstructured":"Organisation for Economic Co-operation and Development: Recommendation of the council on artificial intelligence. Published on 22\/05\/2019. Amended on 03\/05\/2024 (2019). https:\/\/legalinstruments.oecd.org\/en\/instruments\/OECD-LEGAL-0449"},{"key":"39_CR18","doi-asserted-by":"publisher","unstructured":"Ribeiro, M.T., 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. KDD \u201916, Association for Computing Machinery, New York (2016). https:\/\/doi.org\/10.1145\/2939672.2939778","DOI":"10.1145\/2939672.2939778"},{"key":"39_CR19","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., 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, San Francisco, August 13-17, 2016, pp. 1135\u20131144 (2016)","DOI":"10.1145\/2939672.2939778"},{"key":"39_CR20","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: Anchors: high-precision model-agnostic explanations. In: Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence and Thirtieth Innovative Applications of Artificial Intelligence Conference and Eighth AAAI Symposium on Educational Advances in Artificial Intelligence. AAAI\u201918\/IAAI\u201918\/EAAI\u201918, AAAI Press (2018)","DOI":"10.1609\/aaai.v32i1.11491"},{"key":"39_CR21","doi-asserted-by":"publisher","unstructured":"Rjoub, G., et al.: A survey on explainable artificial intelligence for cybersecurity. IEEE Trans. Netw. Serv. Manage. 20, 5115\u20135140 (2023). https:\/\/doi.org\/10.1109\/TNSM.2023.3282740","DOI":"10.1109\/TNSM.2023.3282740"},{"key":"39_CR22","series-title":"Human\u2013Computer Interaction Series","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1007\/978-3-319-90403-0_9","volume-title":"Human and Machine Learning","author":"M Robnik-\u0160ikonja","year":"2018","unstructured":"Robnik-\u0160ikonja, M., Bohanec, M.: Perturbation-based explanations of prediction models. In: Zhou, J., Chen, F. (eds.) Human and Machine Learning. HIS, pp. 159\u2013175. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-90403-0_9"},{"issue":"1","key":"39_CR23","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1007\/s11036-021-01843-0","volume":"27","author":"M Sarhan","year":"2021","unstructured":"Sarhan, M., Layeghy, S., Portmann, M.: Towards a standard feature set for network intrusion detection system datasets. Mobile Netw. Appl. 27(1), 357\u2013370 (2021). https:\/\/doi.org\/10.1007\/s11036-021-01843-0","journal-title":"Mobile Netw. Appl."},{"key":"39_CR24","unstructured":"Selvaraju, R.R., Das, A., Vedantam, R., Cogswell, M., Parikh, D., Batra, D.: Grad-cam: why did you say that? visual explanations from deep networks via gradient-based localization. CoRR abs\/1610.02391 (2016). http:\/\/arxiv.org\/abs\/1610.02391"},{"key":"39_CR25","doi-asserted-by":"publisher","unstructured":"Siganos, M., et al.: Explainable AI-based intrusion detection in the internet of things. In: 18th International Conference on Availability, Reliability and Security (ARES), Benevento, ITALY, AUG 29-SEP 01, pp. 1\u201310. ACM (2023). https:\/\/doi.org\/10.1145\/3600160.3605162","DOI":"10.1145\/3600160.3605162"},{"key":"39_CR26","doi-asserted-by":"publisher","unstructured":"Uysal, I., Kose, U.: Analysis of network intrusion detection via explainable artificial intelligence: applications with shap and lime. In: 2024 Cyber Awareness and Research Symposium (CARS), pp.\u00a01\u20136 (2024). https:\/\/doi.org\/10.1109\/CARS61786.2024.10778742","DOI":"10.1109\/CARS61786.2024.10778742"},{"key":"39_CR27","doi-asserted-by":"crossref","unstructured":"Wachter, S., Mittelstadt, B.D., Russell, C.: Counterfactual explanations without opening the black box: automated decisions and the GDPR. CoRR abs\/1711.00399 (2017). http:\/\/arxiv.org\/abs\/1711.00399","DOI":"10.2139\/ssrn.3063289"},{"key":"39_CR28","doi-asserted-by":"publisher","first-page":"12305","DOI":"10.1002\/int.23088","volume":"37","author":"F Yan","year":"2022","unstructured":"Yan, F., Wen, S., Nepal, S., Paris, C., Xiang, Y.: Explainable machine learning in cybersecurity: a survey. Int. J. Intell. Syst. 37, 12305\u201312334 (2022). https:\/\/doi.org\/10.1002\/int.23088","journal-title":"Int. J. Intell. Syst."}],"container-title":["Lecture Notes in Networks and Systems","Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2025), Volume 2"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-16995-2_39","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T23:42:11Z","timestamp":1775691731000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-16995-2_39"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032169945","9783032169952"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-16995-2_39","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"value":"2367-3370","type":"print"},{"value":"2367-3389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"1 April 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"UCAmI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Ubiquitous Computing and Ambient Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Florence","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","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 November 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 November 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ucami2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ucami.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}