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{"key"=>"Campanile2023301", "type"=>"Conference paper", "bibtex"=>"@conference{Campanile2023301,\n author = {Campanile, Lelio and De Biase, Maria Stella and De Fazio, Roberta and Di Giovanni, Michele and Marulli, Fiammetta and Verde, Laura},\n title = {Merging Model-Based and Data-Driven Approaches for Resilient Systems Digital Twins Design},\n year = {2023},\n journal = {Proceedings of the 2023 IEEE International Conference on Cyber Security and Resilience, CSR 2023},\n pages = {301 – 306},\n doi = {10.1109/CSR57506.2023.10224945}\n}\n", "author"=>"Campanile, Lelio and De Biase, Maria Stella and De Fazio, Roberta and Di Giovanni, Michele and Marulli, Fiammetta and Verde, Laura", "author_array"=>[{"first"=>"Lelio", "last"=>"Campanile", "prefix"=>"", "suffix"=>""}, {"first"=>"Maria Stella", "last"=>"De Biase", "prefix"=>"", "suffix"=>""}, {"first"=>"Roberta", "last"=>"De Fazio", "prefix"=>"", "suffix"=>""}, {"first"=>"Michele", "last"=>"Di Giovanni", "prefix"=>"", "suffix"=>""}, {"first"=>"Fiammetta", "last"=>"Marulli", "prefix"=>"", "suffix"=>""}, {"first"=>"Laura", "last"=>"Verde", "prefix"=>"", "suffix"=>""}], "author_0_first"=>"Lelio", "author_0_last"=>"Campanile", "author_0_prefix"=>"", "author_0_suffix"=>"", "author_1_first"=>"Maria Stella", "author_1_last"=>"De Biase", "author_1_prefix"=>"", "author_1_suffix"=>"", "author_2_first"=>"Roberta", "author_2_last"=>"De Fazio", "author_2_prefix"=>"", "author_2_suffix"=>"", "author_3_first"=>"Michele", "author_3_last"=>"Di Giovanni", "author_3_prefix"=>"", "author_3_suffix"=>"", "author_4_first"=>"Fiammetta", "author_4_last"=>"Marulli", "author_4_prefix"=>"", "author_4_suffix"=>"", "author_5_first"=>"Laura", "author_5_last"=>"Verde", "author_5_prefix"=>"", "author_5_suffix"=>"", "title"=>"Merging Model-Based and Data-Driven Approaches for Resilient Systems Digital Twins Design", "year"=>"2023", "journal"=>"Proceedings of the 2023 IEEE International Conference on Cyber Security and Resilience, CSR 2023", "pages"=>"301 – 306", "doi"=>"10.1109/CSR57506.2023.10224945", "url"=>"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171753139&doi=10.1109%2fCSR57506.2023.10224945&partnerID=40&md5=35e5eb0bfbb092e953335dd83b1b5b34", "abstract"=>"Nowadays, the problem of system robustness, es-pecially in critical infrastructures, is a challenging open question. Some systems provide crucial services continuously failing, threatening the availability of the provided services. By designing a robust architecture, this criticality could be overcome or limited, ensuring service continuity. The definition of a resilient system involves not only its architecture but also the methodology implemented for the calculation and analysis of some indices, quantifying system performance. This study provides an innovative architecture for Digital Twins implementation based on a hybrid methodology for improving the control system in realtime. The introduced approach brings together different techniques. In particular, the work combines the point of strengths of Model-based methods and Data-driven ones, aiming to improve system performances. © 2023 IEEE.", "author_keywords"=>"Digital Twins; Process Mining; Requirement Engineering; Resilience Indices", "keywords"=>"Criticality (nuclear fission); Data-driven approach; Model-based OPC; Modeling data; Process mining; Requirement engineering; Resilience index; Resilient systems; System robustness; Systems performance; Twin design; Computer architecture", "publication_stage"=>"Final", "source"=>"Scopus", "note"=>"Cited by: 3"}