Iskanje po katalogu digitalne knjižnice

Opis: This handbook is a product of the Erasmus+ Strategic Partnership between the partners Université Polytéchnique Hauts-de-France, Politechnika Poznanska, Brandenburgische Technische Universität Cottbus-Senftenberg and the coordinator University of Maribor. Contentuous contribution were made by staff of University of Maribor and Politechnika Poznanska, evaluations by staff of the other two partners. The handbooks handles virtual learning environments in the international education and research area and exposure of the systems to cybercrime. Besides introductory contributions on legal aspects of challenges in the fields of human rights, European regulations of data security, civil law and criminal law aspects of caber security of virtual learning environments and methodologies of their introduction w8ithin organisations, the handbook also gives useful instructions for elaboration of virtual courses within virtual learning environments relevant for the internationalised research and education not only since the Covid-19 pandemic. The handbook is dedicated to use on the internet within the Moodle system.
Ključne besede: cyber security, virtual learning environment, data security, cyber crime, systems
Objavljeno v DKUM: 13.04.2023; Ogledov: 91; Prenosov: 9
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Opis: Background: Medical data are gold mines for deriving the knowledge that could change the course of a single patient’s life or even the health of the entire population. A data analyst needs to have full access to relevant data, but full access may be denied by privacy and confidentiality of medical data legal regulations, especially when the data analyst is not affiliated with the data owner. Objective: Our first objective was to analyze the privacy and confidentiality issues and the associated regulations pertaining to medical data, and to identify technologies to properly address these issues. Our second objective was to develop a procedure to protect medical data in such a way that the outsourced analyst would be capable of doing analyses on protected data and the results would be comparable, if not the same, as if they had been done on the original data. Specifically, our hypothesis was there would not be a difference between the outsourced decision trees built on encrypted data and the ones built on original data. Methods: Using formal definitions, we developed an algorithm to protect medical data for outsourced analyses. The algorithm was applied to publicly available datasets (N=30) from the medical and life sciences fields. The analyses were performed on the original and the protected datasets and the results of the analyses were compared. Bootstrapped paired t tests for 2 dependent samples were used to test whether the mean differences in size, number of leaves, and the accuracy of the original and the encrypted decision trees were significantly different. Results: The decision trees built on encrypted data were virtually the same as those built on original data. Out of 30 datasets, 100% of the trees had identical accuracy. The size of a tree and the number of leaves was different only once (1/30, 3%, P=.19). Conclusions: The proposed algorithm encrypts a file with plain text medical data into an encrypted file with the data protected in such a way that external data analyses are still possible. The results show that the results of analyses on original and on protected data are identical or comparably similar. The approach addresses the privacy and confidentiality issues that arise with medical data and is adherent to strict legal rules in the United States and Europe regarding the processing of the medical data.
Ključne besede: medical data, disclosure control, medical confidentiality, data analysis, data security
Objavljeno v DKUM: 02.08.2017; Ogledov: 1005; Prenosov: 159
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Ključne besede: electronic commerce, government, administration, budgets, democration, computer application, users, electronic money, electronic payments, security, data analysis, information system, information science, business, commerce, models, advertising, Internet, computer networks, electronic mail, services, media, public services, regional policy, cases, retail trade
Objavljeno v DKUM: 01.06.2012; Ogledov: 1985; Prenosov: 47
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Opis: In the paper, we present an algorithm that can be applied to protect data before a data mining process takes place. The data mining, a part of the knowledge discovery process, is mainly about building models from data. We address the following question: can we protect the data and still allow the data modelling process to take place? We consider the case where the distributions of original data values are preserved while the values themselves change, so that the resulting model is equivalent to the one built with original data. The presented formal approach is especially useful when the knowledge discovery process is outsourced. The application of the algorithm is demonstrated through an example.
Ključne besede: data protection algorithm, classification algorithm, disclosure control, data mining, knowledge discovery, data security
Objavljeno v DKUM: 01.06.2012; Ogledov: 1983; Prenosov: 51
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