STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Combining fuzzy information from multiple systems (extended abstract)
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
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
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
An optimal algorithm for approximate nearest neighbor searching
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
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
LOF: identifying density-based local outliers
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Multidimensional binary search trees used for associative searching
Communications of the ACM
Cryptography: Theory and Practice
Cryptography: Theory and Practice
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
Constructions and Bounds for Unconditionally Secure Non-Interactive Commitment Schemes
Designs, Codes and Cryptography
A Multistep Approach for Shape Similarity Search in Image Databases
IEEE Transactions on Knowledge and Data Engineering
When Is ''Nearest Neighbor'' Meaningful?
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Approximate Nearest Neighbor Searching in Multimedia Databases
Proceedings of the 17th International Conference on Data Engineering
Nearest Neighbor Classification in 3D Protein Databases
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
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
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
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
Privacy-Preserving Outlier Detection
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Privately computing a distributed k-nn classifier
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Privacy-Preserving Top-k Queries
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Fast Approximate Similarity Search in Extremely High-Dimensional Data Sets
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Random-data perturbation techniques and privacy-preserving data mining
Knowledge and Information Systems
Privacy-preserving clustering with distributed EM mixture modeling
Knowledge and Information Systems
Privacy Preserving Data Mining (Advances in Information Security)
Privacy Preserving Data Mining (Advances in Information Security)
On the Power of Nonlinear Secret-Sharing
SIAM Journal on Discrete Mathematics
Privacy preservation for data cubes
Knowledge and Information Systems
Singular value decomposition based data distortion strategy for privacy protection
Knowledge and Information Systems
Handicapping attacker's confidence: an alternative to k-anonymization
Knowledge and Information Systems
Fairplay—a secure two-party computation system
SSYM'04 Proceedings of the 13th conference on USENIX Security Symposium - Volume 13
A domain-specific programming language for secure multiparty computation
Proceedings of the 2007 workshop on Programming languages and analysis for security
Privacy Preserving Nearest Neighbor Search
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
The privacy of k-NN retrieval for horizontal partitioned data: new methods and applications
ADC '07 Proceedings of the eighteenth conference on Australasian database - Volume 63
Top 10 algorithms in data mining
Knowledge and Information Systems
Privacy-preserving SVM classification
Knowledge and Information Systems
Protocols for secure computations
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Privacy preserving DBSCAN for vertically partitioned data
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
An efficient and verifiable solution to the millionaire problem
ICISC'04 Proceedings of the 7th international conference on Information Security and Cryptology
On private scalar product computation for privacy-preserving data mining
ICISC'04 Proceedings of the 7th international conference on Information Security and Cryptology
Statistical secrecy and multibit commitments
IEEE Transactions on Information Theory
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Finding the nearest k objects to a query object is a fundamental operation for many data mining algorithms. With the recent interest in privacy, it is not surprising that there is strong interest in k-NN queries to enable clustering, classification and outlier-detection tasks. However, previous approaches to privacy-preserving k-NN have been costly and can only be realistically applied to small data sets. In this paper, we provide efficient solutions for k-NN queries for vertically partitioned data. We provide the first solution for the L ∞ (or Chessboard) metric as well as detailed privacy-preserving computation of all other Minkowski metrics. We enable privacy-preserving L ∞ by providing a practical approach to the Yao’s millionaires problem with more than two parties. This is based on a pragmatic and implementable solution to Yao’s millionaires problem with shares. We also provide privacy-preserving algorithms for combinations of local metrics into a global metric that handles the large dimensionality and diversity of attributes common in vertically partitioned data. To manage very large data sets, we provide a privacy-preserving SASH (a very successful data structure for associative queries in high dimensions). Besides providing a theoretical analysis, we illustrate the efficiency of our approach with an empirical evaluation.