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PADM 2009 : 2009 IEEE International Workshop on Privacy Aspects of Data Mining


When Dec 6, 2009 - Dec 6, 2009
Where Miami, Florida, USA
Submission Deadline Jul 17, 2009
Notification Due Sep 8, 2009
Final Version Due Sep 29, 2009
Categories    data mining

Call For Papers

PADM'09: 2009 IEEE International Workshop on Privacy Aspects of Data Mining:
From Theory to Practice

A full-day workshop at the 9th IEEE International Conference on Data Mining

When: December 6th, 2009
Where: Miami, FL, USA


. July 17, 2009: Due date for full workshop papers
. September 8, 2009: Notification of paper acceptance to authors
. September 29, 2009: Submission of Camera-ready papers
. December 6, 2009: Full-day Workshop

The field of computer science has evolved to incorporate intrinsically complex social, organizational, and political environments in which computers are situated. Nowhere is this more apparent, and the influence of data mining professionals more necessary, than in the often debated arena of privacy. There is an ever-increasing demand for the incorporation of new technologies to collect, analyze, and share data on people for a variety of worthwhile endeavors. However, the traditional knowledge discovery process is often at odds with an individual's civil liberties or expectations of privacy. As such, many governments are struggling to set national and international policies on privacy for data mining endeavors. The result is the relationship between privacy and data mining has received significant attention in the popular media.

Computer science research communities, and data mining in particular, have increasingly focused on addressing the seemingly conflicting requirements for privacy and knowledge discovery. From a methodological perspective, computer scientists have proposed various statistical, cryptographic, and databases processing approaches that enable data mining goals without sacrificing the privacy of the individuals to whom the data corresponds. In industry, we have witnessed major corporations, many of which are key supporters of data mining allocating significant resources to study and develop commercial products that address these issues. These efforts have only scratched the surface of the problem-space, and there remain many open research issues for further investigation. While the issues are grounded in the real-world and concern academia, industry, government, and society in general, we have yet to witness significant technology transfer and the application of such techniques to real world environments remains limited. Clearly, there remain significant opportunities and challenges for the design and evaluation of privacy respective data mining applications. In this workshop, we welcome novel research addressing these challenges.

Extended versions of selected papers of PADM'09 will be invited for publication in the journal Transactions on Data Privacy. Details regarding the journal can be found at

The workshop will seek submissions that cover privacy and security aspects of data mining. The workshop is especially interested in papers that focus on applied domains such as healthcare, ubiquitous computing, social networks, and location-based services. The following list provides examples of the types of areas in which we will encourage submissions:

. Biomedical and healthcare data mining privacy
. Cryptographic tools for privacy preserving data mining
. Data mining for intrusion detection
. Data mining for fraud and identify theft prevention
. Homeland security and privacy preserving applications
. Inference and disclosure control for data mining
. Learning algorithms for randomized/perturbed data
. Privacy in e-commerce and user profiling
. Privacy aware access control
. Privacy and security when mining outsourced data
. Privacy aspects of ubiquitous computing systems
. Privacy policy infrastructure, enforcement, and analysis
. Privacy preserving link and social network analysis
. Privacy preserving data aggregation and integration
. Privacy threats due to data mining
. Security and privacy in spatio-temporal data mining
. Trust management for data mining
. Link and friend-of-a-friend (FOAF) mining for trust

Paper submissions are limited to a maximum of 10 pages in the IEEE 2-column format, the same as the camera-ready format (see the IEEE Computer Society Press Proceedings Author Guidelines). All papers will be reviewed by the Program Committee on the basis of technical quality, relevance to data mining, originality, significance, and clarity. A double blind review process will be adopted. Authors should avoid using identifying information in the text of the paper. You are strongly encouraged to print and double check your PDF/PS file before its submission, especially if your paper contains Asian/European language symb (such as Chinese/Korean characters or English letters with European fonts).

All papers should be submitted through the EasyChair conference management system. To submit your paper, login to


Program Co-Chairs
+ Wei Jiang, Missouri University of Science and Technology
+ Murat Kantarcioglu, University of Texas at Dallas
+ Brad Malin, Vanderbilt University

Program Committee
+ Elisa Bertino, Purdue University
+ Chris Clifton, Purdue University
+ Peter Christen, Australian National University
+ Josep Domingo-Ferrer, Rovira i Virgili University
+ Wenliang Du, Syracuse University
+ Khaled El Emam, University of Ottawa
+ Kun Liu, IBM Research
+ Taneli Mielikļæ½inen, Nokia Research
+ Jian Pei, Simon Fraser University
+ Ercan Nergiz, Sabanci University
+ Lisa Singh, Georgetown University
+ Vassilis Verykios, University of Thessaly
+ (additional members to be announced soon)

Any questions regarding the workshop should be directed to the organizers at

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