An efficient probabilistic public key encryption scheme which hides all partial information
Proceedings of CRYPTO 84 on Advances in cryptology
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Secret sharing homomorphisms: keeping shares of a secret secret
Proceedings on Advances in cryptology---CRYPTO '86
A new public key cryptosystem based on higher residues
CCS '98 Proceedings of the 5th ACM conference on Computer and communications security
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
On the design and quantification of privacy preserving data mining algorithms
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Privacy Preserving Data Mining
CRYPTO '00 Proceedings of the 20th Annual International Cryptology Conference on Advances in Cryptology
Tools for privacy preserving distributed data mining
ACM SIGKDD Explorations Newsletter
Privacy preserving mining of association rules
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
On the Privacy Preserving Properties of Random Data Perturbation Techniques
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Deriving private information from randomized data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Privacy Preserving Data Mining (Advances in Information Security)
Privacy Preserving Data Mining (Advances in Information Security)
Privacy-preserving distributed k-means clustering over arbitrarily partitioned data
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Secure set intersection cardinality with application to association rule mining
Journal of Computer Security
Maintaining data privacy in association rule mining
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Protocols for secure computations
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Public-key cryptosystems based on composite degree residuosity classes
EUROCRYPT'99 Proceedings of the 17th international conference on Theory and application of cryptographic techniques
On private scalar product computation for privacy-preserving data mining
ICISC'04 Proceedings of the 7th international conference on Information Security and Cryptology
Bloom filter bootstrap: privacy-preserving estimation of the size of an intersection
DBSec'13 Proceedings of the 27th international conference on Data and Applications Security and Privacy XXVII
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Contingency tables are widely used in many fields to analyze the relationship or infer the association between two or more variables. Indeed, due to their simplicity and ease, they are one of the first methods used to analyze gathered data. Typically, the construction of contingency tables from source data is considered straightforward since all data is supposed to be aggregated at a single party. However, in many cases, the collected data may actually be federated among different parties. Privacy and security concerns may restrict the data owners from free sharing of the raw data. However, construction of the global contingency tables would still be of immense interest. In this paper, we propose techniques for enabling secure construction of contingency tables from both horizontally and vertically partitioned data. Our methods are efficient and secure. We also examine cases where the constructed contingency table may itself leak too much information and discuss potential solutions.