乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,13]],"date-time":"2025-04-13T00:13:09Z","timestamp":1744503189673,"version":"3.37.3"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2023,6,17]],"date-time":"2023-06-17T00:00:00Z","timestamp":1686960000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,17]],"date-time":"2023-06-17T00:00:00Z","timestamp":1686960000000},"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":["SN COMPUT. SCI."],"DOI":"10.1007\/s42979-023-01821-1","type":"journal-article","created":{"date-parts":[[2023,6,17]],"date-time":"2023-06-17T13:01:35Z","timestamp":1687006895000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Intrusion Detection System in Industrial Cyber-Physical System Using Clustered Federated Learning"],"prefix":"10.1007","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4553-2230","authenticated-orcid":false,"given":"Vellingiri","family":"Jayagopal","sequence":"first","affiliation":[]},{"given":"Mohanraj","family":"Elangovan","sequence":"additional","affiliation":[]},{"given":"Saranya Sathasivam","family":"Singaram","sequence":"additional","affiliation":[]},{"given":"Kavitha Bharathi","family":"Shanmugam","sequence":"additional","affiliation":[]},{"given":"Balu","family":"Subramaniam","sequence":"additional","affiliation":[]},{"given":"Srinivasarao","family":"Bhukya","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,17]]},"reference":[{"issue":"10","key":"1821_CR1","doi-asserted-by":"publisher","first-page":"2323","DOI":"10.1108\/IJQRM-06-2021-0174","volume":"39","author":"VA Wankhede","year":"2021","unstructured":"Wankhede VA, Vinodh S. Analysis of barriers of cyber-physical system adoption in small and medium enterprises using interpretive ranking process. Int J Qual Reliabil Manage. 2021;39(10):2323\u201353. https:\/\/doi.org\/10.1108\/IJQRM-06-2021-0174.","journal-title":"Int J Qual Reliabil Manage."},{"key":"1821_CR2","doi-asserted-by":"crossref","unstructured":"Tharini VJ & Vijayarani S. IoT in healthcare: ecosystem, pillars, design challenges, applications, vulnerabilities, privacy, and security concerns. In: Incorporating the Internet of Things in healthcare applications and wearable devices. IGI Global. 2020; p. 1\u201322.","DOI":"10.4018\/978-1-7998-1090-2.ch001"},{"key":"1821_CR3","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1016\/j.jmsy.2020.11.017","volume":"58","author":"DG Pivoto","year":"2021","unstructured":"Pivoto DG, de Almeida LF, da Rosa Righi R, Rodrigues JJ, Lugli AB, Alberti AM. Cyber-physical systems architectures for industrial internet of things applications in Industry 4.0: a literature review. J Manuf Syst. 2021;58:176\u201392.","journal-title":"J Manuf Syst"},{"issue":"5","key":"1821_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3453155","volume":"54","author":"Y Luo","year":"2021","unstructured":"Luo Y, Xiao Y, Cheng L, Peng G, Yao D. Deep learning-based anomaly detection in cyber-physical systems: progress and opportunities. ACM Comput Surv (CSUR). 2021;54(5):1\u201336.","journal-title":"ACM Comput Surv (CSUR)"},{"key":"1821_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.micpro.2020.103201","volume":"77","author":"JPA Yaacoub","year":"2020","unstructured":"Yaacoub JPA, Salman O, Noura HN, Kaaniche N, Chehab A, Malli M. Cyber-physical systems security: limitations, issues and future trends. Microprocess Microsyst. 2020;77: 103201.","journal-title":"Microprocess Microsyst"},{"key":"1821_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.simpat.2020.102151","volume":"105","author":"D Levshun","year":"2020","unstructured":"Levshun D, Chevalier Y, Kotenko I, Chechulin A. Design and verification of a mobile robot based on the integrated model of cyber-Physical systems. Simul Model Pract Theory. 2020;105: 102151.","journal-title":"Simul Model Pract Theory"},{"key":"1821_CR7","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3200127","author":"Y Geng","year":"2022","unstructured":"Geng Y, Chen Y, Ma R, Wei Q, Pan J, Wang J, et al. Defending cyber-physical systems through reverse engineering-based memory sanity check. IEEE Int Things J. 2022. https:\/\/doi.org\/10.1109\/JIOT.2022.3200127.","journal-title":"IEEE Int Things J"},{"key":"1821_CR8","doi-asserted-by":"crossref","unstructured":"Rajawat AS, Bedi P, Goyal SB, Shaw RN & Ghosh A. Reliability analysis in cyber-physical system using deep learning for smart cities industrial IoT network node. In: AI and IoT for smart city applications. Springer, Singapore, 2022; p. 157\u201369.","DOI":"10.1007\/978-981-16-7498-3_10"},{"issue":"4","key":"1821_CR9","doi-asserted-by":"publisher","first-page":"2351","DOI":"10.1109\/COMST.2021.3106669","volume":"23","author":"J Franco","year":"2021","unstructured":"Franco J, Aris A, Canberk B, Uluagac AS. A survey of honeypots and honeynets for internet of things, industrial internet of things, and cyber-physical systems. IEEE Commun Surv Tutor. 2021;23(4):2351\u201383.","journal-title":"IEEE Commun Surv Tutor"},{"issue":"11","key":"1821_CR10","doi-asserted-by":"publisher","first-page":"7802","DOI":"10.1109\/TII.2021.3064881","volume":"17","author":"S Hu","year":"2021","unstructured":"Hu S, Shi Y, Colombo A, Karnouskos S, Li X. Guest editorial: cloud-edge computing for cyber-physical systems and Internet of Things. IEEE Trans Industr Inf. 2021;17(11):7802\u20135.","journal-title":"IEEE Trans Industr Inf"},{"key":"1821_CR11","doi-asserted-by":"crossref","unstructured":"Morris T & Gao W. Industrial control system traffic data sets for intrusion detection research. In: International conference on critical infrastructure protection. Springer, Berlin. 2014; p. 65\u201378.","DOI":"10.1007\/978-3-662-45355-1_5"},{"key":"1821_CR12","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1007\/s42979-021-00848-6","volume":"2","author":"G Parashar","year":"2021","unstructured":"Parashar G, Chaudhary A, Rana A. Systematic mapping study of AI\/machine learning in healthcare and future directions. SN Comput Sci. 2021;2:461. https:\/\/doi.org\/10.1007\/s42979-021-00848-6.","journal-title":"SN Comput Sci"},{"key":"1821_CR13","doi-asserted-by":"publisher","first-page":"492","DOI":"10.1007\/s42979-022-01390-9","volume":"3","author":"RS Rammuni Silva","year":"2022","unstructured":"Rammuni Silva RS, Fernando P. Effective utilization of multiple convolutional neural networks for chest X-ray classification. SN Comput Sci. 2022;3:492. https:\/\/doi.org\/10.1007\/s42979-022-01390-9.","journal-title":"SN Comput Sci"},{"key":"1821_CR14","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1007\/s42979-020-00299-5","volume":"1","author":"MK Beheshti","year":"2020","unstructured":"Beheshti MK, Safi-Esfahani F. BFPF-cloud: applying SVM for byzantine failure prediction to increase availability and failure tolerance in cloud computing. SN Comput Sci. 2020;1:276. https:\/\/doi.org\/10.1007\/s42979-020-00299-5.","journal-title":"SN Comput Sci"},{"key":"1821_CR15","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1007\/s42979-019-0005-0","volume":"1","author":"S Ceri","year":"2020","unstructured":"Ceri S, Pinoli P. Data science for genomic data management: challenges, resources, experiences. SN Comput Sci. 2020;1:5. https:\/\/doi.org\/10.1007\/s42979-019-0005-0.","journal-title":"SN Comput Sci"},{"key":"1821_CR16","doi-asserted-by":"publisher","unstructured":"Pan Z, Geng H, Wei L and Zhao W. Adaptive client model update with reinforcement learning in synchronous federated learning. In: 2022 32nd International Telecommunication Networks and Applications Conference (ITNAC). Wellington, New Zealand, 2022, p. 1\u20133. https:\/\/doi.org\/10.1109\/ITNAC55475.2022.9998360.","DOI":"10.1109\/ITNAC55475.2022.9998360"},{"key":"1821_CR17","doi-asserted-by":"publisher","unstructured":"Aloqaily M, Al Ridhawi I, Karray F and Guizani M. Towards blockchain-based hierarchical federated learning for cyber-physical systems. In: 2022 International Balkan Conference on Communications and Networking (BalkanCom), Sarajevo, Bosnia and Herzegovina. 2022; p. 46\u201350. https:\/\/doi.org\/10.1109\/BalkanCom55633.2022.9900546.","DOI":"10.1109\/BalkanCom55633.2022.9900546"},{"key":"1821_CR18","doi-asserted-by":"publisher","unstructured":"Abidin NZ and Ritahani Ismail A. Federated deep learning for automated detection of diabetic retinopathy. In: 2022 IEEE 8th International Conference on Computing, Engineering and Design (ICCED), Sukabumi, Indonesia. 2022; p. 1\u20135. https:\/\/doi.org\/10.1109\/ICCED56140.2022.10010636.","DOI":"10.1109\/ICCED56140.2022.10010636"},{"issue":"8","key":"1821_CR19","doi-asserted-by":"publisher","first-page":"5615","DOI":"10.1109\/TII.2020.3023430","volume":"17","author":"B Li","year":"2020","unstructured":"Li B, Wu Y, Song J, Lu R, Li T, Zhao L. DeepFed: federated deep learning for intrusion detection in industrial cyber\u2013physical systems. IEEE Trans Industr Inf. 2020;17(8):5615\u201324.","journal-title":"IEEE Trans Industr Inf"},{"key":"1821_CR20","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1016\/j.comcom.2021.09.029","volume":"181","author":"AL Sohaib","year":"2022","unstructured":"Sohaib AL, Fang BXW, Celestine I, Li-li FW, Syed MM, Zhaoyang H, Shahab SB. AI-empowered, blockchain and SDN integrated security architecture for IoT network of cyber-physical systems. Comput. Commun. 2022;181:274\u201383. https:\/\/doi.org\/10.1016\/j.comcom.2021.09.029.","journal-title":"Computer Communications"},{"issue":"4","key":"1821_CR21","doi-asserted-by":"publisher","first-page":"3057","DOI":"10.1109\/JIOT.2022.3151828","volume":"10","author":"Y Lu","year":"2023","unstructured":"Lu Y, Wang D, Obaidat MS, Vijayakumar P, Edge-assisted intelligent device authentication in cyber-physical systems. IEEE Internet Things J. 2023;10(4):3057\u201370. https:\/\/doi.org\/10.1109\/JIOT.2022.3151828.","journal-title":"IEEE Internet Things J"}],"container-title":["SN Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-023-01821-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42979-023-01821-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-023-01821-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,17]],"date-time":"2023-06-17T13:09:05Z","timestamp":1687007345000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42979-023-01821-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,17]]},"references-count":21,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2023,9]]}},"alternative-id":["1821"],"URL":"https:\/\/doi.org\/10.1007\/s42979-023-01821-1","relation":{},"ISSN":["2661-8907"],"issn-type":[{"type":"electronic","value":"2661-8907"}],"subject":[],"published":{"date-parts":[[2023,6,17]]},"assertion":[{"value":"23 February 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 April 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 June 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}}],"article-number":"452"}}