[PET] Call for contributed talk - WODIAC (Workshop on Design Issues for data Anonymization Competition)
gambs.sebastien at uqam.ca
Thu Jun 8 08:30:07 BST 2017
Call for contributed talk - WODIAC (Workshop on Design Issues for data Anonymization Competition)
To prepare for the organization of data anonymization competition, which will be held next year in conjunction with PETS 2018, a workshop will be organized this year to investigate the design issues related to the organization of such a competition called WODIAC (Workshop on Design Issues for data Anonymization Competition). Please see below on and the following link for a more detailed description of the objective of the workshop: https://petsymposium.org/2017/workshop.php
This workshop will be held on July 17, 2017 as part of PETS 2017 (https://petsymposium.org/2017/index.php).
*** If you are interested to give a talk that fits within the scope of the workshop please send us a title and a one or two paragraphs description of our proposed presentation before June 25 to both the following email addresses ***:
-Sébastien Gambs : gambs.sebastien at uqam.ca<mailto:gambs.sebastien at uqam.ca>
-Hiroaki Kikuchi : kikn at meiji.ac.jp<mailto:kikn at meiji.ac.jp>
We are planning to release the detailed program of the workshop by the end of June.
There will be no official proceedings but the expected outcome of the workshop will a set of recommendations and guidelines to establish the competition based on the presentations and exchanges generated during the workshop.
Workshop on Design Issues for a data Anonymization Competition (WODIAC)
Description of the workshop:
The analysis of large scale datasets, often refer to as Big Data, offers the possibility to realize inferences with an unprecedented level of accuracy and details. However, this massive collection of information also raises many privacy issues since most of these datasets contain personal information, which is thus sensitive by nature. As a result, only very few of them are released and available, which limits both our ability to analyze such data to derive useful knowledge that could benefit to the public and the society at large and slows down the innovative services that could emerge from such data. Thus, an important scientific and societal challenge is the design and study anonymization mechanisms that can be used to remove the sensitive information or add uncertainty to a dataset before it is released or before further services are developed on it.
To address this issue, we will organize a data anonymization competition, to be held in conjunction with PETS 2018, to study the strengths and limits of anonymization methods from an empirical perspective. The main objective of this workshop is to investigate the design issues related to the organization of such a competition:
• First, the choice of the privacy model, the privacy metrics as well as the adversary model used are fundamental issues that need to be well thought out to be sure that they really correspond to realistic and grounded measures of privacy. In addition, the choice of the privacy model should also take into account legal considerations such as existing privacy legislations.
• Second, it is also necessary to define the main inference attacks that could be performed by the adversary based on the released data but also on his background knowledge. For instance, de-anonymization attacks can be used to measure the risk of re-identifying of some records but other inference can also be taken into account to evaluate the privacy level achieved (e.g., attribute disclosure).
• Third, the utility measures need also be chosen to meaningfully assess the achievable trade-off between utility and privacy. The utility could be for example quantified in terms of global properties of the dataset or depends on the application for which the anonymized data is used.
• Fourth, the logistical issues surrounding the competition such as data sources, setting, rules, format, platform for supporting the data submission and the evaluation risk as well as the timeline.
The expected outcome of the workshop is a set of recommendations and guidelines to establish the competition.
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