{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T02:18:34Z","timestamp":1743128314814,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031651748"},{"type":"electronic","value":"9783031651755"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-65175-5_32","type":"book-chapter","created":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T14:43:01Z","timestamp":1721918581000},"page":"451-464","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Cross-Validation for\u00a0Detecting Label Poisoning Attacks: A Study on\u00a0Random Forest Algorithm"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7459-0600","authenticated-orcid":false,"given":"Tharindu Lakshan","family":"Yasarathna","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6918-3587","authenticated-orcid":false,"given":"Lankeshwara","family":"Munasinghe","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6430-9558","authenticated-orcid":false,"given":"Harsha","family":"Kalutarage","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4373-2212","authenticated-orcid":false,"given":"Nhien-An","family":"Le-Khac","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,26]]},"reference":[{"key":"32_CR1","doi-asserted-by":"crossref","unstructured":"Anisetti, M., Ardagna, C.A., Balestrucci, A., Bena, N., Damiani, E., Yeun, C.Y.: On the robustness of random forest against untargeted data poisoning: an ensemble-based approach. IEEE Trans. Sustain. Comput. (2023)","DOI":"10.1109\/TSUSC.2023.3293269"},{"key":"32_CR2","doi-asserted-by":"crossref","unstructured":"Apruzzese, G., et\u00a0al.: Addressing adversarial attacks against security systems based on machine learning. In: 2019 11th International Conference on Cyber Conflict (CyCon), vol.\u00a0900, pp. 1\u201318. IEEE (2019)","DOI":"10.23919\/CYCON.2019.8756865"},{"key":"32_CR3","unstructured":"Chakraborty, A., et\u00a0al.: Adversarial attacks and defences: a survey. ArXiv abs\/1810.00069 (2018)"},{"key":"32_CR4","unstructured":"Chang, J.Y., Im, E.G.: Data poisoning attack on random forest classification model. SMA 2020, 17\u201319 September 2020, Jeju, Republic of Korea (2020)"},{"key":"32_CR5","doi-asserted-by":"crossref","unstructured":"Drews, S., et\u00a0al.: Proving data-poisoning robustness in decision trees. In: Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation, pp. 1083\u20131097 (2020)","DOI":"10.1145\/3385412.3385975"},{"key":"32_CR6","doi-asserted-by":"publisher","unstructured":"Alpaydin, E., Kaynak, C.: Optical Recognition of Handwritten Digits. UCI Machine Learning Repository (1998). https:\/\/doi.org\/10.24432\/C50P49","DOI":"10.24432\/C50P49"},{"key":"32_CR7","doi-asserted-by":"crossref","unstructured":"Fan, J., et\u00a0al.: A survey on data poisoning attacks and defenses. In: 2022 7th IEEE International Conference on Data Science in Cyberspace (DSC), pp. 48\u201355. IEEE (2022)","DOI":"10.1109\/DSC55868.2022.00014"},{"key":"32_CR8","unstructured":"Fleury, N., et\u00a0al.: Malware: an overview on threats, detection and evasion attacks. arXiv preprint arXiv:2107.12873 (2021)"},{"key":"32_CR9","unstructured":"Goodfellow, I.J., Shlens, J., Szegedy, C.: Explaining and harnessing adversarial examples (2015)"},{"key":"32_CR10","doi-asserted-by":"crossref","unstructured":"Ji, Y., Bowman, B., Huang, H.H.: Securing malware cognitive systems against adversarial attacks. In: 2019 IEEE International Conference on Cognitive Computing (ICCC), pp.\u00a01\u20139. IEEE (2019)","DOI":"10.1109\/ICCC.2019.00014"},{"key":"32_CR11","doi-asserted-by":"publisher","unstructured":"Mark, H., Reeber Erik, F.G., Jaap, S.: Spambase. UCI Machine Learning Repository (1999). https:\/\/doi.org\/10.24432\/C53G6X","DOI":"10.24432\/C53G6X"},{"issue":"1","key":"32_CR12","doi-asserted-by":"publisher","first-page":"20180060","DOI":"10.1515\/ijb-2018-0060","volume":"15","author":"P Mart\u00ednez-Camblor","year":"2019","unstructured":"Mart\u00ednez-Camblor, P., Pardo-Fern\u00e1ndez, J.C.: The Youden index in the generalized receiver operating characteristic curve context. Int. J. Biostat. 15(1), 20180060 (2019)","journal-title":"Int. J. Biostat."},{"issue":"5","key":"32_CR13","doi-asserted-by":"publisher","first-page":"909","DOI":"10.3390\/app9050909","volume":"9","author":"S Qiu","year":"2019","unstructured":"Qiu, S., Liu, Q., Zhou, S., Wu, C.: Review of artificial intelligence adversarial attack and defense technologies. Appl. Sci. 9(5), 909 (2019)","journal-title":"Appl. Sci."},{"key":"32_CR14","unstructured":"Shafahi, A., et\u00a0al.: Adversarial training for free! arXiv preprint arXiv:1904.12843 (2019)"},{"key":"32_CR15","doi-asserted-by":"crossref","unstructured":"Sharif, M., et\u00a0al.: Accessorize to a crime: real and stealthy attacks on state-of-the-art face recognition. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, pp. 1528\u20131540 (2016)","DOI":"10.1145\/2976749.2978392"},{"key":"32_CR16","doi-asserted-by":"publisher","first-page":"222310","DOI":"10.1109\/ACCESS.2020.3041951","volume":"8","author":"K Shaukat","year":"2020","unstructured":"Shaukat, K., et al.: A survey on machine learning techniques for cyber security in the last decade. IEEE Access 8, 222310\u2013222354 (2020)","journal-title":"IEEE Access"},{"key":"32_CR17","doi-asserted-by":"crossref","unstructured":"Shen, S., et\u00a0al.: AUROR: defending against poisoning attacks in collaborative deep learning systems. In: Proceedings of the 32nd Annual Conference on Computer Security Applications, pp. 508\u2013519 (2016)","DOI":"10.1145\/2991079.2991125"},{"key":"32_CR18","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1007\/978-3-030-67658-2_10","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"D Solans","year":"2021","unstructured":"Solans, D., Biggio, B., Castillo, C.: Poisoning attacks on algorithmic fairness. In: Hutter, F., Kersting, K., Lijffijt, J., Valera, I. (eds.) ECML PKDD 2020. LNCS (LNAI), vol. 12457, pp. 162\u2013177. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-67658-2_10"},{"key":"32_CR19","unstructured":"Suciu, O., et\u00a0al.: When does machine learning $$\\{$$FAIL$$\\}$$? Generalized transferability for evasion and poisoning attacks. In: 27th $$\\{$$USENIX$$\\}$$ Security Symposium ($$\\{$$USENIX$$\\}$$ Security 18), pp. 1299\u20131316 (2018)"},{"key":"32_CR20","doi-asserted-by":"publisher","unstructured":"Tiago, A., Jos, H.: SMS Spam Collection. UCI Machine Learning Repository (2012). https:\/\/doi.org\/10.24432\/C5CC84","DOI":"10.24432\/C5CC84"},{"issue":"2","key":"32_CR21","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1016\/j.dcan.2021.07.009","volume":"8","author":"C Wang","year":"2022","unstructured":"Wang, C., Chen, J., Yang, Y., Ma, X., Liu, J.: Poisoning attacks and countermeasures in intelligent networks: status quo and prospects. Digit. Commun. Netw. 8(2), 225\u2013234 (2022)","journal-title":"Digit. Commun. Netw."},{"key":"32_CR22","doi-asserted-by":"publisher","first-page":"2566","DOI":"10.1109\/TIFS.2021.3058771","volume":"16","author":"S Weerasinghe","year":"2021","unstructured":"Weerasinghe, S., et al.: Defending support vector machines against data poisoning attacks. IEEE Trans. Inf. Forensics Secur. 16, 2566\u20132578 (2021)","journal-title":"IEEE Trans. Inf. Forensics Secur."}],"container-title":["IFIP Advances in Information and Communication Technology","ICT Systems Security and Privacy Protection"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-65175-5_32","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,24]],"date-time":"2024-11-24T20:52:15Z","timestamp":1732481535000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-65175-5_32"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031651748","9783031651755"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-65175-5_32","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"type":"print","value":"1868-4238"},{"type":"electronic","value":"1868-422X"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"26 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SEC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"IFIP International Conference on ICT Systems Security and Privacy Protection","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Edinburgh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"39","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sec2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ifipsec2024.co.uk\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}