Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Jordi Soria-Comas"'
Publikováno v:
2022 IEEE 38th International Conference on Data Engineering (ICDE)
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
In our data world, a host of not necessarily trusted controllers gather data on individual subjects. To preserve her privacy and, more generally, her informational self-determination, the individual has to be empowered by giving her agency on her own
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f2c6515eb55e7253f1eac74315320e8
https://doi.org/10.1109/icde53745.2022.00135
https://doi.org/10.1109/icde53745.2022.00135
Publikováno v:
Bioinformatics.
Motivation Detailed patient data are crucial for medical research. Yet, these healthcare data can only be released for secondary use if they have undergone anonymization. Results We present and describe µ-ANT, a practical and easily configurable ano
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71b84c5b6f2cae9789c04d5379363dfb
https://doi.org/10.1093/bioinformatics/btz792
https://doi.org/10.1093/bioinformatics/btz792
Publikováno v:
Modeling Decisions for Artificial Intelligence-16th International Conference, MDAI 2019, Milan, Italy, September 4–6, 2019, Proceedings
Modeling Decisions for Artificial Intelligence ISBN: 9783030267728
MDAI
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Modeling Decisions for Artificial Intelligence
Modeling Decisions for Artificial Intelligence ISBN: 9783030267728
MDAI
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Modeling Decisions for Artificial Intelligence
Microaggregation is a well-known family of statistical disclosure control methods, that can also be used to achieve the k-anonymity privacy model and some of its extensions. Microaggregation can be viewed as a clustering problem where clusters must i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9117efd7f768c075ffa3df4ac8cb1820
Publikováno v:
2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
TrustCom/BigDataSE
TrustCom/BigDataSE
Data sharing is key in a wide range of activities but raises serious privacy concerns when the data contain personal information. Anonymization mechanisms provide ways to transform the data so that identities and/or sensitive data are not disclosed (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4af78d01d9381913020019cef2893d4e
Publikováno v:
IEEE Transactions on Information Forensics and Security
As data grow in quantity and complexity, data anonymization is becoming increasingly challenging. On one side, a great diversity of masking methods, synthetic data generation methods, and privacy models exists, and this diversity is often perceived a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e8070fb4b6509b41887e85e2c3cf756
Publikováno v:
Information Sciences. :159-175
We study the design of self-enforcing P2P protocols under the umbrella of co-utility.We study how reputation mechanisms can solve obstacles in co-utile protocol design.We propose a distributed reputation management model based on EigenTrust.We demons
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48bf212b28755082e7185a25966583ee
https://doi.org/10.1016/j.ins.2016.05.050
https://doi.org/10.1016/j.ins.2016.05.050
Publikováno v:
Progress in Artificial Intelligence. 5:105-110
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2534847b719dc006e5d9be2795040e5
https://doi.org/10.1007/s13748-016-0083-3
https://doi.org/10.1007/s13748-016-0083-3
Publikováno v:
Synthesis Lectures on Information Security, Privacy, and Trust. 8:1-136
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36fd1b257f709b33eeab8db69bcc27de
https://doi.org/10.2200/s00690ed1v01y201512spt015
https://doi.org/10.2200/s00690ed1v01y201512spt015
Publikováno v:
Modeling Decisions for Artificial Intelligence ISBN: 9783030002015
MDAI
MDAI
The anonymization of structured data has been widely studied in recent years. However, anonymizing unstructured data (typically text documents) remains a highly manual task and needs more attention from researchers. The main difficulty when dealing w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1636ba722bc6443539d3423232169cf
https://doi.org/10.1007/978-3-030-00202-2_24
https://doi.org/10.1007/978-3-030-00202-2_24
Publikováno v:
ICDM Workshops
2017 IEEE International Conference on Data Mining Workshops (ICDMW)
2017 IEEE International Conference on Data Mining Workshops (ICDMW)
The data anonymization landscape has become quite complex in the last decades. On the methodology side, the statistical disclosure control methods designed in official statistics have been supplemented by a number of privacy models proposed by comput
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36db97d0e90fc8a085f361eed997b580
https://doi.org/10.1109/icdmw.2017.141
https://doi.org/10.1109/icdmw.2017.141