113 search results - page 1 / 23 » Practical privacy: the SuLQ framework |
PODS
2005
ACM
14 years 5 months ago
2005
ACM
USS
2010
2010
P4P: Practical Large-Scale Privacy-Preserving Distributed Computation Robust against Malicious Users
13 years 2 months ago
In this paper we introduce a framework for privacypreserving distributed computation that is practical for many real-world applications. The framework is called Peers for Privacy ...
DMIN
2009
13 years 2 months ago
2009
While the emerging field of privacy preserving data mining (PPDM) will enable many new data mining applications, it suffers from several practical difficulties. PPDM algorithms are...
SDM
2008
SIAM
13 years 6 months ago
2008
SIAM
In this paper we explore private computation built on vector addition and its applications in privacypreserving data mining. Vector addition is a surprisingly general tool for imp...
ESORICS
2008
Springer
13 years 6 months ago
2008
Springer
Gathering and processing sensitive data is a difficult task. In fact, there is no common recipe for building the necessary information systems. In this paper, we present a provably...