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PADM 2011 : 3rd IEEE International Workshop on Privacy Aspects of Data Mining

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Link: http://www.zurich.ibm.com/padm2011
 
When Dec 10, 2011 - Dec 10, 2011
Where Vancouver, Canada
Submission Deadline Jul 23, 2011
Categories    data mining   privacy
 

Call For Papers

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Call for Papers --- PADM 2011

3rd IEEE International Workshop on Privacy Aspects of Data Mining
(in conjunction with ICDM 2011, December 10, 2011, Vancouver, Canada)
http://www.zurich.ibm.com/padm2011/
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IMPORTANT DATES

* Workshop paper submission deadline: ** July 23, 2011 (11:59pm Hawaii time) **
* Workshop paper acceptance notification: September 20, 2011
* Workshop paper camera-ready deadline: October 11, 2011


OVERVIEW

Machine learning and data mining algorithms have now penetrated our everyday lives in a wide range of applications,
like web search, social networking, communication networks, mobility data, advertising, cloud computing, and business
intelligence. Each application can have its own privacy requirements, which include protection of personal information
and statistical disclosure control, protection of business secrets, and knowledge hiding in general. Adaptations of
traditional privacy definitions such as randomized response, k-anonymity, and differential privacy to these new applications
do not always adequately protect sensitive information. Attacks on supposedly anonymized data and additional privacy issues
raised in the literature have shown that developing a robust privacy definition for a new application requires a tremendous
feat of engineering. Another challenge in privacy preserving data analysis is maintaining accuracy (or utility) of the
algorithms. There is an inherent trade-off between privacy and utility which needs to be formally captured for each data
mining task. Often, the utility guarantee provided by an algorithm is dependent on the privacy notion it satisfies. Comparing
the utilities of algorithms that implement different privacy definitions is still an open challenge. Where theoretical utility
analysis is difficult or impossible, it is important to develop performance and data benchmarks, facilitating reliable
comparison of competing methods. Finally, there is a need to address the new privacy challenges presented by emerging applications
such as mobility data mining, social network analysis, advertising, and cloud computing.

PADM will be a full-day workshop that will be held in conjunction with the IEEE ICDM 2011 conference in Vancouver, Canada. The
purpose of this workshop is to encourage principled research that develops methodologies to address open privacy problems.


TOPICS OF INTEREST

The topics of interest include, but are not limited to, the following areas:

* Disclosure prevention of sensitive information when the attacker has detailed knowledge about the privacy mechanisms
* Design guidelines for privacy definitions
* Measuring/comparing utility across different privacy definitions
* Techniques for analyzing perturbed data (e.g. uncertain data analysis)
* Privacy under simultaneous, independent leakages or prior release of information (composition)
* Statistical disclosure control and privacy in social and physical sciences
* Information-theoretic or computational barriers to privacy and utility
* Privacy preservation against data manipulation prior to anonymization
* Privacy preservation using knowledge hiding
* Privacy challenges in emerging applications such as mobility, cloud computing, advertising, and social networking
* Privacy challenges in location-based social networks (e.g. Foursquare, Gowalla)
* Benchmarks and data sets for testing privacy preserving algorithms in emerging application areas


SUBMISSION GUIDELINES

Paper submissions should be limited to a maximum of 8 pages in the IEEE 2-column format. All papers will be double-blind reviewed
by the Program Committee on the basis of technical quality, relevance to privacy aspects of data mining, originality, significance,
and clarity. Papers that have already been accepted or are currently under review for other conferences or journals will not be
considered for PADM 2011.

The authors of a small number of selected (best) papers from the workshop will be invited to prepare a substantially revised and
extended version of their work for publication to a special issue that will be organized after the workshop.


WORKSHOP ORGANIZERS

* Raghav Bhaskar, Microsoft Research, India
* Aris Gkoulalas-Divanis, IBM Research-Zurich, Switzerland
* Dan Kifer, Pennsylvania State University, USA
* Srivatsan Laxman, Microsoft Research, India


PROGRAM COMMITTEE

* Chris Clifton, Purdue University, USA
* Josep Domingo-Ferrer, Universitat Rovira i Virgili, Catalonia
* Michael Hay, Cornell University, USA
* Panos Kalnis, King Abdullah University of Science and Technology, Saudi Arabia
* Hillol Kargupta, University of Maryland Baltimore County, USA
* Kun Liu, Yahoo! Labs, California, USA
* Grigorios Loukides, Vanderbilt University, USA
* Ashwin Machanavajjhala, Yahoo! Research, USA
* Frank McSherry, Microsoft Research, USA
* Gerome Miklau, University of Massachusetts, Amherst, USA
* Mohamed Mokbel, University of Minnesota, USA
* Mehmet Sayal, Hewlett Packard, USA
* Yucel Saygin, Sabanci University, Turkey
* Aleksandra Slavkovic, Penn State University, USA
* Adam Smith, Penn State University, USA
* Trian Marius Truta, Northern Kentucky University, USA
* Philip S. Yu, University of Illinois at Chicago, USA
* Jaideep Vaidya, Rutgers University, USA
* Li Xiong, Emory University, USA


More information about PADM 2011 can be found at: http://www.zurich.ibm.com/padm2011/
Questions should be directed to the workshop co-chairs at: padm2011.workshop gmail.com

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