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» Computing arbitrary functions of encrypted data
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ICDE
1999
IEEE
139views Database» more  ICDE 1999»
16 years 1 months ago
Clustering Large Datasets in Arbitrary Metric Spaces
Clustering partitions a collection of objects into groups called clusters, such that similar objects fall into the same group. Similarity between objects is defined by a distance ...
Venkatesh Ganti, Raghu Ramakrishnan, Johannes Gehr...
101
Voted
CCS
2010
ACM
14 years 12 months ago
Modeling attacks on physical unclonable functions
We show in this paper how several proposed Physical Unclonable Functions (PUFs) can be broken by numerical modeling attacks. Given a set of challenge-response pairs (CRPs) of a PU...
Ulrich Rührmair, Frank Sehnke, Jan Sölte...
ICIP
2009
IEEE
16 years 21 days ago
Secure Distortion Computation Among Untrusting Parties Using Homomorphic Encryption
Alice and Bob possess sequences xn and yn respectively and would like to compute d(xn , yn ) where d(., .) is a distortion measure. However, Alice and Bob do not trust each other ...
176
Voted
GIS
2009
ACM
16 years 22 days ago
Efficient and Secure Distribution of Massive Geo-Spatial Data
Modern geographic databases can contain a large volume of data that need to be distributed to subscribed customers. The data can be modeled as a cube, where typical dimensions inc...
Hao Yuan, Mikhail J. Atallah
SAC
2002
ACM
14 years 11 months ago
A comprehensive model for arbitrary result extraction
Within the realms of workflow management and grid computing, scheduling of distributed services is a central issue. Most schedulers balance time and cost to fit within a client�...
Neal Sample, Dorothea Beringer, Gio Wiederhold