{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T17:33:24Z","timestamp":1778693604063,"version":"3.51.4"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031632105","type":"print"},{"value":"9783031632112","type":"electronic"}],"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\/978-3-031-63211-2_24","type":"book-chapter","created":{"date-parts":[[2024,6,20]],"date-time":"2024-06-20T14:02:22Z","timestamp":1718892142000},"page":"316-329","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Enhancing Malware Detection Through Machine Learning Using XAI with SHAP Framework"],"prefix":"10.1007","author":[{"given":"Nihala","family":"Basheer","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bernardi","family":"Pranggono","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shareeful","family":"Islam","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Spyridon","family":"Papastergiou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haralambos","family":"Mouratidis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,6,21]]},"reference":[{"key":"24_CR1","unstructured":"Number of malware attacks per year 2022 | Statista. Statista (2023). https:\/\/www.statista.com\/statistics\/873097\/malware-attacks-per-year-worldwide\/"},{"key":"24_CR2","doi-asserted-by":"publisher","unstructured":"Fiore, B., Ha, K., Huynh, L., Falcon, J., Vendiola, R., Li, Y.: Security analysis of ransomware: a deep dive into WannaCry and Locky. In: 2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, pp. 285\u2013294 (2023). https:\/\/doi.org\/10.1109\/CCWC57344.2023.10099114","DOI":"10.1109\/CCWC57344.2023.10099114"},{"issue":"3A","key":"24_CR3","doi-asserted-by":"publisher","first-page":"505","DOI":"10.34028\/iajit\/20\/3a\/8","volume":"20","author":"M Grebovic","year":"2023","unstructured":"Grebovic, M., Filipovic, L., Katnic, I., Vukotic, M., Popovic, T.: Machine learning models for statistical analysis. Int. Arab J. Inf. Technol. 20(3A), 505\u2013514 (2023). https:\/\/doi.org\/10.34028\/iajit\/20\/3a\/8","journal-title":"Int. Arab J. Inf. Technol."},{"key":"24_CR4","doi-asserted-by":"publisher","first-page":"25237","DOI":"10.1109\/access.2023.3255176","volume":"11","author":"H Manthena","year":"2023","unstructured":"Manthena, H., Kimmell, J.C., Abdelsalam, M., Gupta, M.: Analyzing and explaining Black-Box models for online malware detection. IEEE Access 11, 25237\u201325252 (2023). https:\/\/doi.org\/10.1109\/access.2023.3255176","journal-title":"IEEE Access"},{"key":"24_CR5","doi-asserted-by":"publisher","unstructured":"Broll, B., Grover, S.: Beyond black-boxes: teaching complex machine learning ideas through scaffolded interactive activities. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, no. 13, pp. 15990\u201315998 (2023). https:\/\/doi.org\/10.1609\/aaai.v37i13.26898","DOI":"10.1609\/aaai.v37i13.26898"},{"key":"24_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1007\/978-3-319-31153-1_11","volume-title":"Applications of Evolutionary Computation","author":"M Gaudesi","year":"2016","unstructured":"Gaudesi, M., Marcelli, A., Sanchez, E., Squillero, G., Tonda, A.: Challenging anti-virus through evolutionary malware obfuscation. In: Squillero, G., Burelli, P. (eds.) EvoApplications 2016. LNCS, vol. 9598, pp. 149\u2013162. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-31153-1_11"},{"key":"24_CR7","doi-asserted-by":"publisher","unstructured":"Alenezi, M.N., Alabdulrazzaq, H., Alshaher, A.A., Alkharang, M.M.: Evolution of malware threats and techniques: a review. Int. J. Commun. Netw. Inf. Secur. (IJCNIS) 12(3), 326\u2013337 (2020). https:\/\/doi.org\/10.54039\/ijcnis.v12i3.4723","DOI":"10.54039\/ijcnis.v12i3.4723"},{"key":"24_CR8","doi-asserted-by":"publisher","unstructured":"Sahay, S.K., Sharma, A.: A survey on the detection of windows desktops malware. In: Advances in Intelligent Systems and Computing (2019). https:\/\/doi.org\/10.1007\/978-981-13-5934-7_14","DOI":"10.1007\/978-981-13-5934-7_14"},{"key":"24_CR9","unstructured":"Yegneswaran, V., Barford, P., Jha, S.: Global intrusion detection in the DOMINO overlay System. In: Network and Distributed System Security Symposium (2004). https:\/\/www.isoc.org\/isoc\/conferences\/ndss\/04\/proceedings\/Papers\/Yegneswaran.pdf"},{"issue":"2","key":"24_CR10","doi-asserted-by":"publisher","first-page":"7","DOI":"10.5120\/15544-4098","volume":"90","author":"A Sharma","year":"2014","unstructured":"Sharma, A., Sahay, S.K.: Evolution and detection of polymorphic and metamorphic malwares: a survey. Int. J. Comput. Appl. 90(2), 7\u201311 (2014). https:\/\/doi.org\/10.5120\/15544-4098","journal-title":"Int. J. Comput. Appl."},{"key":"24_CR11","doi-asserted-by":"publisher","first-page":"1199","DOI":"10.1109\/TNSM.2022.3200741","volume":"20","author":"A Shaukat","year":"2023","unstructured":"Shaukat, A., Omar, A., Farman, A., Muhammad, I., Tamer, A.: Effective multitask deep learning for IoT malware detection and identification using behavioral traffic analysis. IEEE Trans. Netw. Serv. Manag. 20, 1199\u20131209 (2023). https:\/\/doi.org\/10.1109\/TNSM.2022.3200741","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"24_CR12","doi-asserted-by":"publisher","unstructured":"Bharadiya, J.P.: Machine learning in cybersecurity: techniques and challenges. Eur. J. Technol. 7(2), 1\u201314 (2023). https:\/\/doi.org\/10.47672\/ejt.1486","DOI":"10.47672\/ejt.1486"},{"key":"24_CR13","doi-asserted-by":"publisher","unstructured":"Schultz, M.G., Eskin, E., Zadok, F., Stolfo, S.J.: Data mining methods for detection of new malicious executables. In: Proceedings 2001 IEEE Symposium on Security and Privacy. S&P 2001, Oakland, CA, USA, pp. 38\u201349 (2001). https:\/\/doi.org\/10.1109\/SECPRI.2001.924286","DOI":"10.1109\/SECPRI.2001.924286"},{"issue":"4","key":"24_CR14","doi-asserted-by":"publisher","first-page":"35","DOI":"10.3390\/BDCC2040035","volume":"2","author":"K Demertzis","year":"2018","unstructured":"Demertzis, K., Kikiras, P., Tziritas, N., Sanchez, S.L., Iliadis, L.: The next generation cognitive security operations center: network flow forensics using cybersecurity intelligence. Big Data Cogn. Comput. 2(4), 35 (2018). https:\/\/doi.org\/10.3390\/BDCC2040035","journal-title":"Big Data Cogn. Comput."},{"key":"24_CR15","doi-asserted-by":"publisher","unstructured":"Firdausi, I., Lim, C., Erwin, A., Nugroho, A.S.: Analysis of machine learning techniques used in behavior-based malware detection. In: 2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies, Jakarta, Indonesia, pp. 201\u2013203 (2010). https:\/\/doi.org\/10.1109\/ACT.2010.33","DOI":"10.1109\/ACT.2010.33"},{"key":"24_CR16","doi-asserted-by":"publisher","first-page":"769","DOI":"10.1007\/978-3-030-79150-6_60","volume-title":"Artificial Intelligence Applications and Innovations: 17th IFIP WG 12.5 International Conference, AIAI 2021, Hersonissos, Crete, Greece, June 25\u201327, 2021, Proceedings","author":"K Demertzis","year":"2021","unstructured":"Demertzis, K., Iliadis, L., Pimenidis, E., Tziritas, N., Koziri, M., Kikiras, P., Tonkin, M.: Federated blockchained supply chain management: a cybersecurity and privacy framework. In: Maglogiannis, I., Macintyre, J., Iliadis, L. (eds.) Artificial Intelligence Applications and Innovations: 17th IFIP WG 12.5 International Conference, AIAI 2021, Hersonissos, Crete, Greece, June 25\u201327, 2021, Proceedings, pp. 769\u2013779. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-79150-6_60"},{"issue":"11","key":"24_CR17","doi-asserted-by":"publisher","first-page":"6839","DOI":"10.3390\/app13116839","volume":"13","author":"J Jo","year":"2023","unstructured":"Jo, J., Cho, J., Moon, J.: A malware detection and extraction method for the related information using the VIT attention mechanism on Android operating system. Appl. Sci. 13(11), 6839 (2023). https:\/\/doi.org\/10.3390\/app13116839","journal-title":"Appl. Sci."},{"key":"24_CR18","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/978-3-030-79157-5_18","volume-title":"Artificial Intelligence Applications and Innovations. AIAI 2021 IFIP WG 12.5 International Workshops: 5G-PINE 2021, AI-BIO 2021, DAAI 2021, DARE 2021, EEAI 2021, and MHDW 2021, Hersonissos, Crete, Greece, June 25\u201327, 2021, Proceedings","author":"K Demertzis","year":"2021","unstructured":"Demertzis, K., Iliadis, L., Kikiras, P.: A lipschitz - shapley explainable defense methodology against adversarial attacks. In: Maglogiannis, I., Macintyre, J., Iliadis, L. (eds.) Artificial Intelligence Applications and Innovations. AIAI 2021 IFIP WG 12.5 International Workshops: 5G-PINE 2021, AI-BIO 2021, DAAI 2021, DARE 2021, EEAI 2021, and MHDW 2021, Hersonissos, Crete, Greece, June 25\u201327, 2021, Proceedings, pp. 211\u2013227. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-79157-5_18"},{"key":"24_CR19","doi-asserted-by":"publisher","DOI":"10.1002\/spy2.312","author":"P Kumar","year":"2023","unstructured":"Kumar, P., et al.: Explainable artificial intelligence envisioned security mechanisms for cyber threat hunting. Secur. Priv. (2023). https:\/\/doi.org\/10.1002\/spy2.312","journal-title":"Secur. Priv."},{"key":"24_CR20","doi-asserted-by":"publisher","unstructured":"Poddar, S., Chowdhury, D., Dwivedi, A.D., Mukkamala, R.R.: Data driven based malicious URL detection using explainable AI. In: 2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Wuhan, China, pp. 1266\u20131272 (2022). https:\/\/doi.org\/10.1109\/TrustCom56396.2022.00176","DOI":"10.1109\/TrustCom56396.2022.00176"},{"key":"24_CR21","unstructured":"PacktPublishing. Mastering-Machine-Learning-for-Penetration-Testing\/Chapter03\/MalwareData.csv.gz at master. PacktPublishing\/Mastering-Machine-Learning-for-Penetration-Testing. GitHub (2018). https:\/\/github.com\/PacktPublishing\/Mastering-Machine-Learning-for-Penetration-Testing\/blob\/master\/Chapter03\/MalwareData.csv.gz"},{"key":"24_CR22","doi-asserted-by":"publisher","first-page":"e0287705","DOI":"10.1371\/journal.pone.0287705","volume":"18","author":"M Kerrie","year":"2023","unstructured":"Kerrie, M., Benoit, L.: SMOTE-CD: SMOTE for compositional data. PLoS ONE 18, e0287705 (2023). https:\/\/doi.org\/10.1371\/journal.pone.0287705","journal-title":"PLoS ONE"},{"key":"24_CR23","doi-asserted-by":"crossref","unstructured":"Aslam, W., Fraz, M.M., Rizvi, S.K., Saleem, S.: Cross-validation of machine learning algorithms for malware detection using static features of Windows portable executables: a Comparative Study (2020)","DOI":"10.1109\/HONET50430.2020.9322809"},{"key":"24_CR24","doi-asserted-by":"publisher","unstructured":"Obi, J.C.: A comparative study of several classification metrics and their performances on data. World J. Adv. Eng. Technol. Sci, 8, 308\u2013314 (2023). https:\/\/doi.org\/10.30574\/wjaets.2023.8.1.0054","DOI":"10.30574\/wjaets.2023.8.1.0054"},{"key":"24_CR25","doi-asserted-by":"crossref","unstructured":"Islam, S., Abba, A., Ismail, U., Mouratidis, H., Papastergiou, S.: Vulnerability prediction for secure healthcare supply chain service delivery. In: Integrated Computer-Aided Engineering. IOS Press (2022)","DOI":"10.3233\/ICA-220689"}],"container-title":["IFIP Advances in Information and Communication Technology","Artificial Intelligence Applications and Innovations"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-63211-2_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,20]],"date-time":"2024-06-20T14:04:13Z","timestamp":1718892253000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-63211-2_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031632105","9783031632112"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-63211-2_24","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"value":"1868-4238","type":"print"},{"value":"1868-422X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"21 June 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"IFIP International Conference on Artificial Intelligence Applications and Innovations","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Corfu","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":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aiai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ifipaiai.org\/2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}