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» Empirical models of privacy in location sharing
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KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 7 months ago
Privacy-Preserving Data Mining through Knowledge Model Sharing
Privacy-preserving data mining (PPDM) is an important topic to both industry and academia. In general there are two approaches to tackling PPDM, one is statistics-based and the oth...
Patrick Sharkey, Hongwei Tian, Weining Zhang, Shou...
LOCWEB
2009
ACM
14 years 1 months ago
Binding privacy rules to location on the web
As a tool for mitigating the potential privacy risks of gathering and transmitting location information on the Web, we suggest in this paper a model for conveying location informa...
Alissa Cooper, John Morris
CCS
2010
ACM
13 years 6 months ago
Protecting location privacy against inference attacks
GPS-enabled mobile devices are a quickly growing market and users are starting to share their location information with each other through services such as Google Latitude. Locati...
Kazuhiro Minami, Nikita Borisov
OOPSLA
2010
Springer
13 years 5 months ago
Cross-language, type-safe, and transparent object sharing for co-located managed runtimes
As software becomes increasingly complex and difficult to analyze, it is more and more common for developers to use high-level, type-safe, object-oriented (OO) programming langua...
Michal Wegiel, Chandra Krintz
CIDM
2007
IEEE
14 years 1 months ago
Privacy Preserving Burst Detection of Distributed Time Series Data Using Linear Transforms
— In this paper, we consider burst detection within the context of privacy. In our scenario, multiple parties want to detect a burst in aggregated time series data, but none of t...
Lisa Singh, Mehmet Sayal