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» Privacy and Contextual Integrity: Framework and Applications
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CCS
2010
ACM
14 years 9 months ago
HyperSentry: enabling stealthy in-context measurement of hypervisor integrity
This paper presents HyperSentry, a novel framework to enable integrity measurement of a running hypervisor (or any other highest privileged software layer on a system). Unlike exi...
Ahmed M. Azab, Peng Ning, Zhi Wang, Xuxian Jiang, ...
99
Voted
DMIN
2009
180views Data Mining» more  DMIN 2009»
14 years 7 months ago
APHID: A Practical Architecture for High-Performance, Privacy-Preserving Data Mining
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...
Jimmy Secretan, Anna Koufakou, Michael Georgiopoul...
CORR
2010
Springer
130views Education» more  CORR 2010»
14 years 9 months ago
Towards Adaptable and Adaptive Policy-Free Middleware
We believe that to fully support adaptive distributed applications, middleware must itself be adaptable, adaptive and policy-free. In this paper we present a new language-independ...
Alan Dearle, Graham N. C. Kirby, Stuart J. Norcros...
70
Voted
ACSAC
2001
IEEE
15 years 1 months ago
A JCA-Based Implementation Framework for Threshold Cryptography
The Java Cryptography Architecture, JCA in short, was created to allow JCA-compliant cryptography providers to be plugged into a JCA-aware application at run time. This configurab...
Yih Huang, David Rine, Xunhua Wang
KDD
2004
ACM
159views Data Mining» more  KDD 2004»
15 years 2 months ago
Optimal randomization for privacy preserving data mining
Randomization is an economical and efficient approach for privacy preserving data mining (PPDM). In order to guarantee the performance of data mining and the protection of individ...
Michael Yu Zhu, Lei Liu