DOI Publisher Details
{"key"=>"Barzegar2024147", "type"=>"Conference paper", "bibtex"=>"@conference{Barzegar2024147,\n author = {Barzegar, Atrin and Campanile, Lelio and Marrone, Stefano and Marulli, Fiammetta and Verde, Laura and Mastroianni, Michele},\n title = {Fuzzy-based Severity Evaluation in Privacy Problems: An Application to Healthcare},\n year = {2024},\n journal = {Proceedings - 2024 19th European Dependable Computing Conference, EDCC 2024},\n pages = {147 – 154},\n doi = {10.1109/EDCC61798.2024.00037}\n}\n", "author"=>"Barzegar, Atrin and Campanile, Lelio and Marrone, Stefano and Marulli, Fiammetta and Verde, Laura and Mastroianni, Michele", "author_array"=>[{"first"=>"Atrin", "last"=>"Barzegar", "prefix"=>"", "suffix"=>""}, {"first"=>"Lelio", "last"=>"Campanile", "prefix"=>"", "suffix"=>""}, {"first"=>"Stefano", "last"=>"Marrone", "prefix"=>"", "suffix"=>""}, {"first"=>"Fiammetta", "last"=>"Marulli", "prefix"=>"", "suffix"=>""}, {"first"=>"Laura", "last"=>"Verde", "prefix"=>"", "suffix"=>""}, {"first"=>"Michele", "last"=>"Mastroianni", "prefix"=>"", "suffix"=>""}], "author_0_first"=>"Atrin", "author_0_last"=>"Barzegar", "author_0_prefix"=>"", "author_0_suffix"=>"", "author_1_first"=>"Lelio", "author_1_last"=>"Campanile", "author_1_prefix"=>"", "author_1_suffix"=>"", "author_2_first"=>"Stefano", "author_2_last"=>"Marrone", "author_2_prefix"=>"", "author_2_suffix"=>"", "author_3_first"=>"Fiammetta", "author_3_last"=>"Marulli", "author_3_prefix"=>"", "author_3_suffix"=>"", "author_4_first"=>"Laura", "author_4_last"=>"Verde", "author_4_prefix"=>"", "author_4_suffix"=>"", "author_5_first"=>"Michele", "author_5_last"=>"Mastroianni", "author_5_prefix"=>"", "author_5_suffix"=>"", "title"=>"Fuzzy-based Severity Evaluation in Privacy Problems: An Application to Healthcare", "year"=>"2024", "journal"=>"Proceedings - 2024 19th European Dependable Computing Conference, EDCC 2024", "pages"=>"147 – 154", "doi"=>"10.1109/EDCC61798.2024.00037", "url"=>"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194891259&doi=10.1109%2fEDCC61798.2024.00037&partnerID=40&md5=8b12d5afe5d9ffb9fd8e34175a208ba6", "abstract"=>"The growing diffusion of smart pervasive applications is starting to mine personal privacy: from Internet of Things to Machine Learning, the opportunities for privacy loss are many. As for other concerns involving people and goods as financial, safety and security, researchers and practitioners have defined in time different risk assessment procedures to have repeatable and accurate ways of detecting, quantifying and managing the (possible) source of privacy loss. This paper defines a methodology to deal with privacy risk assessment, overcoming the traditional dichotomy between qualitative (easy to apply) and quantitative (accurate) approaches. The present paper introduces an approach based on fuzzy logic, able to conjugate the benefits of both techniques. The feasibility of the proposed methodology is demonstrated using a healthcare case study. © 2024 IEEE.", "author_keywords"=>"Fuzzy Inference; Healthcare; Privacy Risk Assessment; Smart Pervasive Applications", "keywords"=>"Fuzzy inference; Health care; Fuzzy inferencer; Healthcare; Machine-learning; Personal privacy; Pervasive applications; Privacy problems; Privacy risk assessment; Privacy risks; Risks assessments; Smart pervasive application; Risk assessment", "publication_stage"=>"Final", "source"=>"Scopus", "note"=>"Cited by: 3"}