Data Privacy

Home Topics Book Talks Publications Links Conferences History

Data Privacy

Content:	This page includes slides from different talks (seminars and plenary talks). There is another page with slides related to my book: V. Torra (2022) Guide to data privacy: Models, Technologies, Solutions. Springer. Link to Springer Slides, code, etc. here
Uppsala:	Talk at Cybersecurity Arena, Uppsala University Data privacy: From centralized learning to federated learning.
Manchester:	Talk at the Department of Computer Science, University of Manchester -- Announcement and abstract here Privacy models for machine learning and statistics.
IEC:	Talk at the Catalan National Accademy -- Institute of Catalan Studies, Society of Science and Tecnology Aprenentatge automàtic que preserva la privadesa.
FrAIdays Umeå:	Talk on "Research directions on data privacy" at #frAiday talks. Research directions on data privacy.
CRT Foundations of Data Science:	Lecture for the second session in the Foundations of Data Science II training. Data privacy. An introduction. Data privacy. Research lines.
IEEE Chapter (Webinar):	Webinar for the IEEE Computer Society Chapter Sweden on May 31st, 2018. It presents an introduction to data privacy, discusses different privacy models (e.g., k-anonymity, differential privacy, and reidentification), and tools to provide solutions that are compliant to the privacy models. We will also discuss some research issues we are involved in. Data privacy. A briefer.
NAV (Oslo):	Talk at NAV in Oslo on January 15th, 2018. Introduction to data privacy. The talk included examples of data protection in R. Protection of microdata (masking methods) and of tabular data. We used sdcMicro and sdcTable. Slides, code and example file used. Main talk. Data privacy: introduction. Talk on using R. Data privacy: sdcMicro and sdcTable Code in R using both sdcMicro and sdcTable Example file used for tabular data protection in R (sdcTable)
DPM2017:	Keynote talk in DPM 2017: Privacy models and disclosure risk: integral privacy. Keynote talk
HiS2017:	Data privacy: an introduction. Talk given in the U. of Skovde on February 2017. part I (Klara Stokes) part II (Vicenç Torra)
Linköping 2016:	Short summary: How to use machine learning to evaluate the worst-case disclosure risk scenario, and what is the role of transparency in disclosure risk assessment. On machine learning for data privacy.
IFIP2016:	This talk was about how to deal with data privacy in big data, from the point of view of data anonymization (data masking). The talk presents a few directions for future research. The talk was given in the IFIP Summer School 2016 (program here). Big data privacy and anonymization A full paper corresponding to this talk is being published by Springer. V. Torra, G. Navarro-Arribas (2016) Big Data Privacy and Anonymization, in A: Lehmann et al., Privacy and Identity Management 2016, IFIP AICT 498. Read it here (open access).
Uppsala 2016:	Short summary: How to use machine learning to evaluate the worst-case disclosure risk scenario, and what is the role of transparency in disclosure risk assessment. Data privacy: supervised approaches for disclosure risk assessment.
Chalmers 2015:	Short summary: How to use machine learning to evaluate the worst-case disclosure risk scenario, and what is the role of transparency in disclosure risk assessment. Disclosure risk assessment and transparency attacks in data privacy.
PAIS 2015:	Discussion on how transparency affects disclosure risk. When any release applies the transparency principle, we inform users on how the data has been processed (protected), and they can use this information to attack data more effectively. Information on the transparency principle can be found here. Transparency and disclosure risk in data privacy.