{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T21:15:34Z","timestamp":1742937334126,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031578526"},{"type":"electronic","value":"9783031578533"}],"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\/978-3-031-57853-3_40","type":"book-chapter","created":{"date-parts":[[2024,4,9]],"date-time":"2024-04-09T04:01:52Z","timestamp":1712635312000},"page":"476-486","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Automotive User Interface Based on\u00a0LSTM-Grid Search Deep Learning Model for\u00a0IoT Security Change Request Classification"],"prefix":"10.1007","author":[{"given":"Zaineb","family":"Sakhrawi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Taher","family":"Labidi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Asma","family":"Sellami","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nadia","family":"Bouassida","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,4,10]]},"reference":[{"issue":"3","key":"40_CR1","doi-asserted-by":"publisher","first-page":"1646","DOI":"10.1109\/COMST.2020.2988293","volume":"22","author":"MA Al-Garadi","year":"2020","unstructured":"Al-Garadi, M.A., et al.: A survey of machine and deep learning methods for internet of things (IoT) security. IEEE Commun. Surv. Tutor. 22(3), 1646\u20131685 (2020)","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"40_CR2","doi-asserted-by":"publisher","first-page":"886","DOI":"10.1007\/s13198-016-0546-8","volume":"8","author":"M Haoues","year":"2017","unstructured":"Haoues, M., Sellami, A., Ben-Abdallah, H., Cheikhi, L.: A guideline for software architecture selection based on ISO 25010 quality related characteristics. Int. J. Syst. Assur. Eng. Manag. 8, 886\u2013909 (2017)","journal-title":"Int. J. Syst. Assur. Eng. Manag."},{"key":"40_CR3","doi-asserted-by":"crossref","unstructured":"Medhat, N., Moussa, S., Badr, N., Tolba, M.F.: Testing techniques in IoT-based systems. In: 2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS), December 2019, pp. 394\u2013401. IEEE (2019)","DOI":"10.1109\/ICICIS46948.2019.9014711"},{"issue":"1","key":"40_CR4","doi-asserted-by":"publisher","first-page":"16","DOI":"10.3390\/electronics11010016","volume":"11","author":"W Ahmad","year":"2021","unstructured":"Ahmad, W., Rasool, A., Javed, A.R., Baker, T., Jalil, Z.: Cyber security in IoT-based cloud computing: a comprehensive survey. Electronics 11(1), 16 (2021)","journal-title":"Electronics"},{"key":"40_CR5","doi-asserted-by":"publisher","first-page":"215716","DOI":"10.1109\/ACCESS.2020.3039931","volume":"8","author":"N Medhat","year":"2020","unstructured":"Medhat, N., Moussa, S.M., Badr, N.L., Tolba, M.F.: A framework for continuous regression and integration testing in IoT systems based on deep learning and search-based techniques. IEEE Access 8, 215716\u2013215726 (2020)","journal-title":"IEEE Access"},{"issue":"1","key":"40_CR6","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1109\/JAS.2022.105860","volume":"10","author":"X Feng","year":"2022","unstructured":"Feng, X., Zhu, X., Han, Q.L., Zhou, W., Wen, S., Xiang, Y.: Detecting vulnerability on IoT device firmware: a survey. IEEE\/CAA J. Automatica Sin. 10(1), 25\u201341 (2022)","journal-title":"IEEE\/CAA J. Automatica Sin."},{"key":"40_CR7","doi-asserted-by":"publisher","first-page":"106877","DOI":"10.1016\/j.infsof.2022.106877","volume":"147","author":"O AlDhafer","year":"2022","unstructured":"AlDhafer, O., Ahmad, I., Mahmood, S.: An end-to-end deep learning system for requirements classification using recurrent neural networks. Inf. Softw. Technol. 147, 106877 (2022)","journal-title":"Inf. Softw. Technol."},{"key":"40_CR8","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1007\/s11277-021-09124-5","volume":"123","author":"S Zhu","year":"2021","unstructured":"Zhu, S., Yang, S., Gou, X., Xu, Y., Zhang, T., Wan, Y.: Survey of testing methods and testbed development concerning internet of things. Wirel. Pers. Commun. 123, 165\u2013194 (2021). https:\/\/doi.org\/10.1007\/s11277-021-09124-5","journal-title":"Wirel. Pers. Commun."},{"key":"40_CR9","unstructured":"Johnson, R. Zhang, T.: Supervised and semi-supervised text categorization using LSTM for region embeddings. In: International Conference on Machine Learning, pp. 526\u2013534. PMLR (2016)"},{"key":"40_CR10","doi-asserted-by":"crossref","unstructured":"Navarro-Almanza, R., Juarez-Ramirez, R., Licea, G.: Towards supporting software engineering using deep learning: a case of software requirements classification. In: 2017 5th International Conference in Software Engineering Research and Innovation (CONISOFT), pp. 116\u2013120. IEEE (2017)","DOI":"10.1109\/CONISOFT.2017.00021"},{"issue":"5","key":"40_CR11","doi-asserted-by":"publisher","first-page":"3089","DOI":"10.3390\/app13053089","volume":"13","author":"J Han","year":"2023","unstructured":"Han, J., Pak, W.: Hierarchical LSTM-based network intrusion detection system using hybrid classification. Appl. Sci. 13(5), 3089 (2023)","journal-title":"Appl. Sci."},{"issue":"5","key":"40_CR12","doi-asserted-by":"publisher","first-page":"1258","DOI":"10.3390\/electronics12051258","volume":"12","author":"AE Yahya","year":"2023","unstructured":"Yahya, A.E., Gharbi, A., Yafooz, W.M., Al-Dhaqm, A.: A novel hybrid deep learning model for detecting and classifying non-functional requirements of mobile apps issues. Electronics 12(5), 1258 (2023)","journal-title":"Electronics"},{"issue":"10","key":"40_CR13","doi-asserted-by":"publisher","first-page":"1264","DOI":"10.3390\/e23101264","volume":"23","author":"N Rahimi","year":"2021","unstructured":"Rahimi, N., Eassa, F., Elrefaei, L.: One-and two-phase software requirement classification using ensemble deep learning. Entropy 23(10), 1264 (2021)","journal-title":"Entropy"},{"issue":"3","key":"40_CR14","doi-asserted-by":"publisher","first-page":"1434","DOI":"10.3390\/en16031434","volume":"16","author":"N Bacanin","year":"2023","unstructured":"Bacanin, N., Stoean, C., Zivkovic, M., Rakic, M., Strulak-W\u00f3jcikiewicz, R., Stoean, R.: On the benefits of using metaheuristics in the hyperparameter tuning of deep learning models for energy load forecasting. Energies 16(3), 1434 (2023)","journal-title":"Energies"},{"key":"40_CR15","doi-asserted-by":"crossref","unstructured":"Kim, T.Y., Cho, S.B.: Particle swarm optimization-based CNN-LSTM networks for forecasting energy consumption. In: 2019 IEEE Congress on Evolutionary Computation (CEC), pp. 1510\u20131516. IEEE (2019)","DOI":"10.1109\/CEC.2019.8789968"},{"issue":"12","key":"40_CR16","doi-asserted-by":"publisher","first-page":"13911","DOI":"10.1007\/s11227-021-03838-w","volume":"77","author":"I Priyadarshini","year":"2021","unstructured":"Priyadarshini, I., Cotton, C.: A novel LSTM-CNN-grid search-based deep neural network for sentiment analysis. J. Supercomput. 77(12), 13911\u201313932 (2021)","journal-title":"J. Supercomput."},{"issue":"4","key":"40_CR17","doi-asserted-by":"publisher","first-page":"042077","DOI":"10.1088\/1742-6596\/1529\/4\/042077","volume":"1529","author":"S Tiun","year":"2020","unstructured":"Tiun, S., Mokhtar, U.A., Bakar, S.H., Saad, S.: Classification of functional and non-functional requirement in software requirement using Word2vec and fast Text. J. Phys. Conf. Ser. 1529(4), 042077 (2020)","journal-title":"J. Phys. Conf. Ser."}],"container-title":["Lecture Notes on Data Engineering and Communications Technologies","Advanced Information Networking and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-57853-3_40","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,9]],"date-time":"2024-04-09T04:07:23Z","timestamp":1712635643000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-57853-3_40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031578526","9783031578533"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-57853-3_40","relation":{},"ISSN":["2367-4512","2367-4520"],"issn-type":[{"type":"print","value":"2367-4512"},{"type":"electronic","value":"2367-4520"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"10 April 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AINA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Information Networking and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kitakyushu","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","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":"17 April 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 April 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"38","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aina2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/voyager.ce.fit.ac.jp\/conf\/aina\/2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}