{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T09:09:12Z","timestamp":1784365752085,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":19,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819234226","type":"print"},{"value":"9789819234233","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"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":[[2027]]},"DOI":"10.1007\/978-981-92-3423-3_4","type":"book-chapter","created":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T08:45:08Z","timestamp":1784364308000},"page":"36-47","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["RIFT: A Burst-Aware and Log-Horizon Transformer for Ransomware Detection"],"prefix":"10.1007","author":[{"given":"Zhilu","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peinan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingbo","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengkai","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Hou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,19]]},"reference":[{"key":"4_CR1","doi-asserted-by":"crossref","unstructured":"Malik, V., Khanna, A., Sharma, N., et al.: Trends in ransomware attacks: analysis and future predictions. Int. J. Global Innov. Solutions (IJGIS) (2024)","DOI":"10.21428\/e90189c8.f2996624"},{"key":"4_CR2","unstructured":"MacColl, J., et al.: The scourge of ransomware: victim insights on harms to individuals, organisations and society (2024)"},{"issue":"11","key":"4_CR3","doi-asserted-by":"publisher","first-page":"5078","DOI":"10.1007\/s13198-024-02496-4","volume":"15","author":"G Kirubavathi","year":"2024","unstructured":"Kirubavathi, G., Regis Anne, W., Sridevi, U.: A recent review of ransomware attacks on healthcare industries. Int. J. Syst. Assur. Eng. Manag. 15(11), 5078\u20135096 (2024)","journal-title":"Int. J. Syst. Assur. Eng. Manag."},{"key":"4_CR4","doi-asserted-by":"crossref","unstructured":"Viddiu, O., Macpherson, G., Vasquez, E., Kamenova, I., Calderon, D.: Automated ransomware detection using windows file system activity monitoring and a novel machine learning approach. Authorea Preprints (2024)","DOI":"10.22541\/au.172893987.71304373\/v1"},{"key":"4_CR5","doi-asserted-by":"publisher","first-page":"103703","DOI":"10.1016\/j.cose.2024.103703","volume":"139","author":"S Gulmez","year":"2024","unstructured":"Gulmez, S., Kakisim, A.G., Sogukpinar, I.: XRan: explainable deep learning-based ransomware detection using dynamic analysis. Comput. Secur. 139, 103703 (2024)","journal-title":"Comput. Secur."},{"key":"4_CR6","doi-asserted-by":"publisher","first-page":"110138","DOI":"10.1016\/j.comnet.2023.110138","volume":"239","author":"M Cen","year":"2024","unstructured":"Cen, M., Jiang, F., Qin, X., Jiang, Q., Doss, R.: Ransomware early detection: a survey. Comput. Netw. 239, 110138 (2024)","journal-title":"Comput. Netw."},{"key":"4_CR7","doi-asserted-by":"crossref","unstructured":"Yan, P., Khoei, T.T., Hyder, R.S., Hyder, R.S.: Comparative analysis of time series deep learning models for detecting ransomware attacks. In: 2025 IEEE 15th Annual Computing and Communication Workshop and Conference (CCWC), pp. 00126\u201300131. IEEE (2025)","DOI":"10.1109\/CCWC62904.2025.10903686"},{"issue":"7","key":"4_CR8","doi-asserted-by":"publisher","first-page":"2079","DOI":"10.3390\/electronics14071245","volume":"14","author":"S Alzahrani","year":"2025","unstructured":"Alzahrani, S., Xiao, Y., Asiri, S., Alasmari, N., Li, T.: RansomFormer: a crossmodal transformer architecture for ransomware detection via the fusion of byte and API features. Electronics 14(7), 2079\u20139292 (2025)","journal-title":"Electronics"},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Shwetha, H., Vineeth, N., Asha, G.: Deep learning approaches for ransomware detection: assessing CNN and CNN-LSTM models using class imbalance methods. In: 2024 2nd International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS), pp. 249\u2013256. IEEE (2024)","DOI":"10.1109\/ICSSAS64001.2024.10760450"},{"issue":"11","key":"4_CR10","doi-asserted-by":"publisher","first-page":"1571","DOI":"10.1109\/TC.2020.3011748","volume":"69","author":"D Meng","year":"2020","unstructured":"Meng, D., et al.: Built-in security computer: deploying security-first architecture using active security processor. IEEE Trans. Comput. 69(11), 1571\u20131583 (2020)","journal-title":"IEEE Trans. Comput."},{"key":"4_CR11","unstructured":"VirusTotal Homepage. https:\/\/www.virustotal.com. Accessed 02 Apr 2026"},{"key":"4_CR12","unstructured":"VirusShare Homepage. https:\/\/virusshare.com. Accessed 02 Apr 2026"},{"key":"4_CR13","unstructured":"MalwareBazaar Homepage. https:\/\/bazaar.abuse.ch\/browse\/. Accessed 02 Apr 2026"},{"key":"4_CR14","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"4_CR15","doi-asserted-by":"crossref","unstructured":"Zhou, H., et al.: Informer: beyond efficient transformer for long sequence time-series forecasting. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 11106\u201311115(2021)","DOI":"10.1609\/aaai.v35i12.17325"},{"key":"4_CR16","unstructured":"Nie, Y., Nguyen, N.H., Sinthong, P., Kalagnanam, J.: A time series is worth 64 words: long-term forecasting with transformers. In: The Eleventh International Conference on Learning Representations (2023)"},{"key":"4_CR17","unstructured":"Liu, Y., et al.: iTransformer: inverted transformers are effective for time series forecasting. In: The Twelfth International Conference on Learning Representations (2024)"},{"key":"4_CR18","doi-asserted-by":"crossref","unstructured":"Zhang, H., Zhao, L., Yu, A., Cai, L., Meng, D.: Ranker: early ransomware detection through kernel-level behavioral analysis. IEEE Trans. Inf. Forensics Secur. (2024)","DOI":"10.1109\/TIFS.2024.3410511"},{"issue":"3","key":"4_CR19","first-page":"600","volume":"72","author":"GO Ganfure","year":"2022","unstructured":"Ganfure, G.O., Wu, C.F., Chang, Y.H., Shih, W.K.: DeepWare: imaging performance counters with deep learning to detect ransomware. IEEE Trans. Comput. 72(3), 600\u2013613 (2022)","journal-title":"IEEE Trans. Comput."}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3423-3_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T08:45:11Z","timestamp":1784364311000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3423-3_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,19]]},"ISBN":["9789819234226","9789819234233"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3423-3_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,19]]},"assertion":[{"value":"19 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toronto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2026a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2026\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}