The 3rd International Workshop on Privacy-Aware
Location-based Mobile Services (PALMS)
In conjunction with the 10th International Conference on Mobile Data Management (MDM'09)

 Taipei, Taiwan, May 18-21, 2009
   
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Workshop Chair
 Xiaofeng Meng

Renmin University of China

 

PC Co-Chair
 XiaoChun Yang

Northeastern University, China

Wei-Shinn Ku

Auburn University, USA

 

PC Members
 

Walid Aref

Purdue University, USA
Louise Barkhuus

University of Glasgow, UK
Alastair Beresford

University of Cambridge, UK
Claudio Bettini

University of Milan, Italy
Lei Chen

Hong Kong University of Science and Technology, Hong Kong
Yu Chen

State University of New York at Binghamton, USA
Reynold Cheng

University of Hong Kong, Hong Kong
Max J. Egenhofer

University of Maine, USA
Marco Gruteser

Rutgers University, USA
Urs Hengartner

University of Waterloo, Canada
Chih-Lin Hu

National Central University, Taiwan
Jiun-Long Huang

National Chiao Tung University, Taiwan
Yoshiharu Ishikawa

Nagoya University, Japan
Eija Kaasinen

VTT Information Technology, Finland
Panos Kalnis

National University of Singapore, Singapore
Lars Kulik

University of Melbourne, Australia
Xuan Liu

IBM T.J. Watson Research Center, USA
Hua Lu

Aalborg University, Denmark
Wen-Chih Peng

National Chiao Tung University, Taiwan
Cyrus Shahabi

University of Southern California, USA
Xiaoyang Sean Wang

University of Vermont, USA
Jianliang Xu

Hong Kong Baptist University, Hong Kong
Baihua Zheng

Singapore Management University, Singapore
Roger Zimmermann

National University of Singapore, Singapore


Previous Workshop

PALMS 2007

PLAMS 2008
Theme of the Workshop

Combining the functionality of location-aware devices, wireless and cellular phone technologies, and data management results in enabling a new era of location-based mobile services that aim to provide personalized services to their customers based on their current locations. Examples of such services include location-aware emergency service, location-based advertisement, live traffic reports, and location-based store finder. Although location-based services promise safety and convenience, they threaten the privacy and security for their customers as they rely mainly on the knowledge of their customers' location information. The current model of location-based services trades the customers' privacy with the service. If a user wants to keep her private location information, she has to turn off her location-aware device and temporarily unsubscribe from the service. Recent social studies show that customers become more privacy-aware as they tend to avoid using location-based services in order to keep their privacy. As a result, there is a real concern that the privacy issues may hinder the technological advances in location-based services.
 
Workshop Goals


Location privacy is a cross cutting area as it crosses social science, communications, location-based services, databases, and security. The main goal of the workshop is to gather scientists from these areas together to foster the collaboration among such interdisciplinary areas and sparkle discussion on open topics related to location privacy.

The workshop aims aim to address the location privacy from different aspects, starting from social studies of users concerns, going through different models of representing location privacy, location anonymization techniques, imprecise locations, query processing for private or imprecise location data, and ending with a study of various attack models for private location data. The workshop aims also to discuss location privacy in various environments that include using GPS, RFID, or sensor networks. The workshop will be organized in a way to allow close interaction among participants and to sparkle discussions and thoughts among various research communities.

 
Workshop Scope

The scope of this workshop includes but is not limited to the following topics:
  • Context-aware Privacy
  • Location data publish models
  • Location-based Services with location privacy
  • Imprecision in Mobile Computing
  • Legislative approaches for protecting location privacy
  • Location Anonymity Techniques
  • Non-intrusive Location Tracking
  • Models for simultaneous provision of security and privacy
  • Privacy attack models
  • Privacy in sensor networks
  • Query Processing for Private Location Data
  • Social Studies for Location Privacy
  • User Perceptive to Location Privacy

Paper Submissions


All submissions must be original unpublished work written in English that is currently not under review at another venue. Submitted papers will be published in IEEE workshop proceedings as 6 pages in IEEE style format. Papers must be submitted via https://cmt.research.microsoft.com/PALMS2009. Submissions of novel ideas and positions that can spark discussion among the attendees are strongly encouraged.

 

Important Dates (Tentative)


Submission deadline: January 30, 2009
Notifications: March 1, 2009

Workshop date: May 21, 2009
 
Last updated: September, 2008 by BAOJIE