STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
An improved algorithm for constructing kth-order voronoi diagrams
IEEE Transactions on Computers
Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
The SR-tree: an index structure for high-dimensional nearest neighbor queries
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
S3: similarity search in CAD database systems
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Scalable access within the context of digital libraries
IEEE ADL '97 Proceedings of the IEEE international forum on Research and technology advances in digital libraries
Principles of multimedia database systems
Principles of multimedia database systems
Proceedings of the 1998 workshop on New security paradigms
Efficient private bidding and auctions with an oblivious third party
CCS '99 Proceedings of the 6th ACM conference on Computer and communications security
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
The Quadtree and Related Hierarchical Data Structures
ACM Computing Surveys (CSUR)
Multidimensional binary search trees used for associative searching
Communications of the ACM
Investigative Data Mining for Security and Criminal Detection
Investigative Data Mining for Security and Criminal Detection
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
A Multistep Approach for Shape Similarity Search in Image Databases
IEEE Transactions on Knowledge and Data Engineering
Nearest Neighbor Classification in 3D Protein Databases
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
The A-tree: An Index Structure for High-Dimensional Spaces Using Relative Approximation
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Efficient Index Structures for String Databases
Proceedings of the 27th International Conference on Very Large Data Bases
Indexing the Distance: An Efficient Method to KNN Processing
Proceedings of the 27th International Conference on Very Large Data Bases
Fast Nearest Neighbor Search in Medical Image Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Privacy preserving association rule mining in vertically partitioned data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting Spatial Knowledge from the Web
SAINT '03 Proceedings of the 2003 Symposium on Applications and the Internet
Building decision tree classifier on private data
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
Privacy-Preserving Cooperative Statistical Analysis
ACSAC '01 Proceedings of the 17th Annual Computer Security Applications Conference
Privacy-preserving k-means clustering over vertically partitioned data
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Navigating massive data sets via local clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Private Representative-Based Clustering for Vertically Partitioned Data
ENC '04 Proceedings of the Fifth Mexican International Conference in Computer Science
Privately computing a distributed k-nn classifier
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Fast Approximate Similarity Search in Extremely High-Dimensional Data Sets
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Privacy preserving DBSCAN for vertically partitioned data
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
Privacy-preserving regression algorithms
SMO'07 Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization
A new efficient privacy-preserving scalar product protocol
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
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Recently, privacy issues have become important in clustering analysis, especially when data is horizontally partitioned over several parties. Associative queries are the core retrieval operation for many data mining algorithms, especially clustering and k-NN classification. The algorithms that efficiently support k-NN queries are of special interest. We show how to adapt well-known data structures to the privacy preserving context and what is the overhead of this adaptation. We present an algorithm for k-NN in secure multiparty computation. This is based on presenting private computation of several metrics. As a result, we can offer three approaches to associative queries over horizontally partitioned data with progressively less security. We show privacy preserving algorithms for data structures that induce a partition on the space; such as KD-Trees. Our next preference is our Privacy Preserving SASH. However, we demonstrate that the most effective approach to achieve privacy is separate data structures for parties, where associative queries work separately, followed by secure combination to produce the overall output. This idea not only enhances security but also reduces communication cost between data holders. Our results and protocols also enable us to improve on previous approaches for k-NN classification.