{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:29:51Z","timestamp":1742912991525,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":10,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819907403"},{"type":"electronic","value":"9789819907410"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-981-99-0741-0_22","type":"book-chapter","created":{"date-parts":[[2023,3,31]],"date-time":"2023-03-31T09:04:34Z","timestamp":1680253474000},"page":"305-315","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SDDLA: A New Architecture for Secured Decentralized Distributed Learning"],"prefix":"10.1007","author":[{"given":"Sufyan","family":"Almajali","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,4,1]]},"reference":[{"key":"22_CR1","doi-asserted-by":"crossref","unstructured":"Almajali, S., Abou-Tair, D.E.D.I.: Cloud based intelligent extensible shared context services. In: 2017 Second International Conference on Fog and Mobile Edge Computing (FMEC). IEEE (2017)","DOI":"10.1109\/FMEC.2017.7946420"},{"issue":"17","key":"22_CR2","doi-asserted-by":"publisher","first-page":"24617","DOI":"10.1007\/s11042-018-7049-3","volume":"78","author":"S Almajali","year":"2018","unstructured":"Almajali, S., Abou-Tair, D., Salameh, H.B., Ayyash, M., Elgala, H.: A distributed multi-layer MEC-cloud architecture for processing large scale IoT-based multimedia applications. Multimed. Tools Appl. 78(17), 24617\u201324638 (2018). https:\/\/doi.org\/10.1007\/s11042-018-7049-3","journal-title":"Multimed. Tools Appl."},{"key":"22_CR3","doi-asserted-by":"crossref","unstructured":"Gao, Y., et al.: End-to-end evaluation of federated learning and split learning for internet of things. In: 2020 International Symposium on Reliable Distributed Systems (SRDS). IEEE (2020)","DOI":"10.1109\/SRDS51746.2020.00017"},{"key":"22_CR4","doi-asserted-by":"crossref","unstructured":"Hamdan, S., Almajali, S., Ayyash, M.: Comparison study between conventional machine learning and distributed multi-task learning models. In: 2020 21st International Arab Conference on Information Technology (ACIT). IEEE (2020)","DOI":"10.1109\/ACIT50332.2020.9300096"},{"key":"22_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.simpat.2022.102685","volume":"122","author":"S Hamdan","year":"2023","unstructured":"Hamdan, S., Almajali, S., Ayyash, M., Salameh, H.B., Jararweh, Y.: An intelligent edge-enabled distributed multi-task learning architecture for large-scale IoT-based cyber\u2013physical systems. Simul. Model. Pract. Theory 122, 102685 (2023)","journal-title":"Simul. Model. Pract. Theory"},{"issue":"22","key":"22_CR6","doi-asserted-by":"publisher","first-page":"6441","DOI":"10.3390\/s20226441","volume":"20","author":"S Hamdan","year":"2020","unstructured":"Hamdan, S., Ayyash, M., Almajali, S.: Edge-computing architectures for internet of things applications: a survey. Sensors 20(22), 6441 (2020)","journal-title":"Sensors"},{"key":"22_CR7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-63913-0","volume-title":"An Introduction to Machine Learning","author":"M Kubat","year":"2017","unstructured":"Kubat, M.: An Introduction to Machine Learning. Springer, Cham (2017)"},{"key":"22_CR8","doi-asserted-by":"crossref","unstructured":"Lu, T., Ai, Q., Lee, W.J., Wang, Z., He, H.: An aggregated decision tree-based learner for renewable integration prediction. In: 2018 IEEE Industry Applications Society Annual Meeting (IAS). IEEE (2018)","DOI":"10.1109\/IAS.2018.8544544"},{"key":"22_CR9","unstructured":"Zenko, B., Todorovski, L., Dzeroski, S.: A comparison of stacking with meta decision trees to bagging, boosting, and stacking with other methods. In: Proceedings 2001 IEEE International Conference on Data Mining. IEEE (2001)"},{"key":"22_CR10","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Yin, L., Peng, Y., Li, D.: A quick survey on large scale distributed deep learning systems. In: 2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS). IEEE (2018)","DOI":"10.1109\/PADSW.2018.8644613"}],"container-title":["Lecture Notes on Data Engineering and Communications Technologies","Data Science and Emerging Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-0741-0_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,30]],"date-time":"2023-05-30T20:51:27Z","timestamp":1685479887000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-0741-0_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819907403","9789819907410"],"references-count":10,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-0741-0_22","relation":{},"ISSN":["2367-4512","2367-4520"],"issn-type":[{"type":"print","value":"2367-4512"},{"type":"electronic","value":"2367-4520"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"1 April 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DaSET","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The International Conference on Data Science and Emerging Technologies","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 December 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 December 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"daset2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icdaset.com","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}