{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:21:08Z","timestamp":1759191668286,"version":"3.44.0"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032060778","type":"print"},{"value":"9783032060785","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"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\/978-3-032-06078-5_8","type":"book-chapter","created":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T18:50:30Z","timestamp":1759171830000},"page":"130-148","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["MalGPT: A Generative Explainable Model for\u00a0Malware Binaries"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2125-2162","authenticated-orcid":false,"given":"Mohd","family":"Saqib","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8423-2906","authenticated-orcid":false,"given":"Benjamin C. M.","family":"Fung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Steven H. H.","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philippe","family":"Charland","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,30]]},"reference":[{"key":"8_CR1","doi-asserted-by":"publisher","unstructured":"Ambekar, N.G., Devi, N.N., Thokchom, S., Yogita: TabLSTMNet: enhancing Android malware classification through integrated attention and explainable AI. Microsyst. Techno., 1\u201319 (2024). https:\/\/doi.org\/10.1007\/s00542-024-05615-0","DOI":"10.1007\/s00542-024-05615-0"},{"key":"8_CR2","doi-asserted-by":"publisher","first-page":"102846","DOI":"10.1016\/j.cose.2022.102846","volume":"121","author":"F Demirk\u0131ran","year":"2022","unstructured":"Demirk\u0131ran, F., \u00c7ay\u0131r, A., \u00dcnal, U., Da\u011f, H.: An ensemble of pre-trained transformer models for imbalanced multiclass malware classification. Comput. Secur. 121, 102846 (2022)","journal-title":"Comput. Secur."},{"key":"8_CR3","doi-asserted-by":"crossref","unstructured":"Herath, J.D., Wakodikar, P.P., Yang, P., Yan, G.: CFGExplainer: explaining graph neural network-based malware classification from control flow graphs. In: 2022 52nd Annual IEEE\/IFIP International Conference on Dependable Systems and Networks (DSN), pp. 172\u2013184. IEEE (2022)","DOI":"10.1109\/DSN53405.2022.00028"},{"key":"8_CR4","doi-asserted-by":"publisher","unstructured":"Khan, I.A., Moustafa, N., Pi, D., Sallam, K.M., Zomaya, A.Y., Li, B.: A new explainable deep learning framework for cyber threat discovery in industrial IoT networks. IEEE Internet Things J. (2021). https:\/\/doi.org\/10.1109\/JIOT.2021.3130156","DOI":"10.1109\/JIOT.2021.3130156"},{"key":"8_CR5","doi-asserted-by":"publisher","unstructured":"Kinkead, M., Millar, S., McLaughlin, N., O\u2019Kane, P.: Towards explainable CNNs for Android malware detection. Proc. Comput. Sci. 184, 959\u2013965 (2021). https:\/\/doi.org\/10.1016\/j.procs.2021.03.118","DOI":"10.1016\/j.procs.2021.03.118"},{"key":"8_CR6","doi-asserted-by":"publisher","unstructured":"Lever, C., Kotzias, P., Balzarotti, D., Caballero, J., Antonakakis, M.: A lustrum of malware network communication and insights. In: 2017 IEEE Symposium on Security and Privacy (SP), pp. 788\u2013804 (2017). https:\/\/doi.org\/10.1109\/SP.2017.59","DOI":"10.1109\/SP.2017.59"},{"key":"8_CR7","doi-asserted-by":"publisher","unstructured":"Li, M.Q., Fung, B.C., Charland, P., Ding, S.H.: $$I-MAD$$: interpretable malware detector using galaxy transformer. Comput. Secur. 108, 102371 (2021). https:\/\/doi.org\/10.1016\/j.cose.2021.102371","DOI":"10.1016\/j.cose.2021.102371"},{"key":"8_CR8","doi-asserted-by":"publisher","unstructured":"Lu, Z., Thing, V.L.: \u201chow does it detect a malicious app?\u201d Explaining the predictions of AI-based malware detector. In: 2022 IEEE 8th International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing,(HPSC) and IEEE International Conference on Intelligent Data and Security (IDS), pp. 194\u2013199. IEEE (2022). https:\/\/doi.org\/10.1109\/BigDataSecurityHPSCIDS54978.2022.00045","DOI":"10.1109\/BigDataSecurityHPSCIDS54978.2022.00045"},{"key":"8_CR9","unstructured":"Lundberg, S.M., Lee, S.I.: A unified approach to interpreting model predictions. In: Proceedings of the 31st International Conference on Neural Information Processing Systems, NIPS 2017, Red Hook, NY, USA, pp. 4768\u20134777. Curran Associates Inc. (2017)"},{"key":"8_CR10","doi-asserted-by":"publisher","unstructured":"Mitchell, J., McLaughlin, N., Martinez-del Rincon, J.: Generating sparse explanations for malicious android opcode sequences using hierarchical lime. Comput. Secur. 137, 103637 (2024). https:\/\/doi.org\/10.1016\/j.cose.2023.103637","DOI":"10.1016\/j.cose.2023.103637"},{"key":"8_CR11","doi-asserted-by":"publisher","unstructured":"Rahali, A., Akhloufi, M.A.: MalBERT: malware detection using bidirectional encoder representations from transformers. In: 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 3226\u20133231 (2021). https:\/\/doi.org\/10.1109\/SMC52423.2021.9659287","DOI":"10.1109\/SMC52423.2021.9659287"},{"key":"8_CR12","doi-asserted-by":"crossref","unstructured":"Reimers, N., Gurevych, I.: Sentence-BERT: sentence embeddings using Siamese BERT-networks. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (2019)","DOI":"10.18653\/v1\/D19-1410"},{"key":"8_CR13","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, KDD 2016, pp. 1135\u20131144. Association for Computing Machinery, New York, NY, USA (2016). https:\/\/doi.org\/10.1145\/2939672.2939778","DOI":"10.1145\/2939672.2939778"},{"key":"8_CR14","doi-asserted-by":"crossref","unstructured":"Saqib, M., Fung, B.C.M., Charland, P., Walenstein, A.: GAGE: genetic algorithm-based graph explainer for malware analysis. In: Proceedings of the 40th IEEE International Conference on Data Engineering (ICDE), Utrecht, Netherlands, pp. 2258\u20132270. IEEE Computer Society (2024)","DOI":"10.1109\/ICDE60146.2024.00179"},{"key":"8_CR15","doi-asserted-by":"publisher","unstructured":"Saqib, M., Mahdavifar, S., Fung, B.C.M., Charland, P.: A comprehensive analysis of explainable AI for malware hunting. ACM Comput. Surv. 56(12) (2024). https:\/\/doi.org\/10.1145\/3677374","DOI":"10.1145\/3677374"},{"key":"8_CR16","doi-asserted-by":"publisher","unstructured":"Smmarwar, S.K., Gupta, G.P., Kumar, S.: XAI-AMD-DL: an explainable AI approach for Android malware detection system using deep learning. In: 2023 IEEE World Conference on Applied Intelligence and Computing (AIC), pp. 423\u2013428. IEEE (2023). https:\/\/doi.org\/10.1109\/AIC57670.2023.10263974","DOI":"10.1109\/AIC57670.2023.10263974"},{"key":"8_CR17","doi-asserted-by":"publisher","unstructured":"To, T.N., Hoang, H.D., Duy, P.T., Pham, V.H.: MalDEX: an explainable malware detection system based on ensemble learning. In: 2023 International Conference on Multimedia Analysis and Pattern Recognition (MAPR), pp.\u00a01\u20136 (2023). https:\/\/doi.org\/10.1109\/MAPR59823.2023.10288922","DOI":"10.1109\/MAPR59823.2023.10288922"},{"issue":"18","key":"8_CR18","doi-asserted-by":"publisher","first-page":"6766","DOI":"10.3390\/s22186766","volume":"22","author":"F Ullah","year":"2022","unstructured":"Ullah, F., Alsirhani, A., Alshahrani, M.M., Alomari, A., Naeem, H., Shah, S.A.: Explainable malware detection system using transformers-based transfer learning and multi-model visual representation. Sensors 22(18), 6766 (2022)","journal-title":"Sensors"},{"key":"8_CR19","doi-asserted-by":"publisher","first-page":"25696","DOI":"10.1109\/ACCESS.2022.3155695","volume":"10","author":"X Xing","year":"2022","unstructured":"Xing, X., Jin, X., Elahi, H., Jiang, H., Wang, G.: A malware detection approach using autoencoder in deep learning. IEEE Access 10, 25696\u201325706 (2022). https:\/\/doi.org\/10.1109\/ACCESS.2022.3155695","journal-title":"IEEE Access"},{"key":"8_CR20","doi-asserted-by":"publisher","unstructured":"Zhang, T., Kishore, V., Wu, F., Weinberger, K.Q., Artzi, Y.: BERTScore: evaluating text generation with BERT. In: Proceedings of the International Conference on Learning Representations (ICLR), New York, NY, USA. Cornell University and ASAPP Inc., Cornell Tech. (2020). https:\/\/doi.org\/10.48550\/arXiv.1904.09675","DOI":"10.48550\/arXiv.1904.09675"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases. Research Track"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-06078-5_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T18:50:33Z","timestamp":1759171833000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-06078-5_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,30]]},"ISBN":["9783032060778","9783032060785"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-06078-5_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,30]]},"assertion":[{"value":"30 September 2025","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":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Porto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","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":"15 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ecmlpkdd.org\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}