Home     Topics     Book     Talks     Publications     Links     Conferences     History            20 20 20

Data Privacy

Privacy Preserving Data Mining (PPDM)

Statistical Disclosure Control (SDC)

http://www.ppdm.cat


Content:
This page includes slides from different talks (seminars and plenary talks). For slides related to my book:
  • V. Torra (2017) Data privacy: Foundations, new developments and the big data challenge, Springer. (Slides here)


Talk @ CRT Foundations of Data Science:
Lecture for the second session in the Foundations of Data Science II training.
Talk @ 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.
Talk @ 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.
Talk @ DPM2017:
Keynote talk in DPM 2017: Privacy models and disclosure risk: integral privacy.
Talk @ HiS2017:
Data privacy: an introduction. Talk given in the U. of Skovde on February 2017.
Talk @ 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.
Invited talk @ 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). 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).

Talk @ 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.
Talk @ 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.
Invited Talk @ 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.


 



Vicenç Torra, Last modified: 12 : 57 February 20 2020.