Privacy Preserving Data Mining
CRYPTO '00 Proceedings of the 20th Annual International Cryptology Conference on Advances in Cryptology
Multiparty Computation from Threshold Homomorphic Encryption
EUROCRYPT '01 Proceedings of the International Conference on the Theory and Application of Cryptographic Techniques: Advances in Cryptology
Privacy preserving association rule mining in vertically partitioned data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and 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 clustering with distributed EM mixture modeling
Knowledge and Information Systems
Privacy-preserving distributed k-means clustering over arbitrarily partitioned data
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Privacy-Preserving Computation of Bayesian Networks on Vertically Partitioned Data
IEEE Transactions on Knowledge and Data Engineering
Secure two-party k-means clustering
Proceedings of the 14th ACM conference on Computer and communications security
Non-interactive Proofs for Integer Multiplication
EUROCRYPT '07 Proceedings of the 26th annual international conference on Advances in Cryptology
Homomorphic Encryption and Signatures from Vector Decomposition
Pairing '08 Proceedings of the 2nd international conference on Pairing-Based Cryptography
Privacy-preserving data mining in the malicious model
International Journal of Information and Computer Security
Public-key cryptosystems based on composite degree residuosity classes
EUROCRYPT'99 Proceedings of the 17th international conference on Theory and application of cryptographic techniques
Public-key encryption with non-interactive opening
CT-RSA'08 Proceedings of the 2008 The Cryptopgraphers' Track at the RSA conference on Topics in cryptology
Evaluating 2-DNF formulas on ciphertexts
TCC'05 Proceedings of the Second international conference on Theory of Cryptography
Efficient set operations in the presence of malicious adversaries
PKC'10 Proceedings of the 13th international conference on Practice and Theory in Public Key Cryptography
Public-key encryption with non-interactive opening: new constructions and stronger definitions
AFRICACRYPT'10 Proceedings of the Third international conference on Cryptology in Africa
Efficient CCA-Secure PKE from identity-based techniques
CT-RSA'10 Proceedings of the 2010 international conference on Topics in Cryptology
Privacy-preserving data mining: a game-theoretic approach
DBSec'11 Proceedings of the 25th annual IFIP WG 11.3 conference on Data and applications security and privacy
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In many distributed data mining settings, disclosure of the original data sets is not acceptable due to privacy concerns. To address such concerns, privacy-preserving data mining has been an active research area in recent years. While confidentiality is a key issue, scalability is also an important aspect to assess the performance of a privacypreserving data mining algorithms for practical applications. With this in mind, Kantarcioglu et al. proposed secure dot product and secure setintersection protocols for privacy-preserving data mining in malicious adversarial model using zero knowledge proofs, since the assumption of semi-honest adversary is unrealistic in some settings. Both the computation and communication complexities are linear with the number of data items in the protocols proposed by Kantarcioglu et al. In this paper, we build efficient and secure dot product and set-intersection protocols in malicious model. In our work, the complexity of computation and communication for proof of knowledge is always constant (independent of the number of data items), while the complexity of computation and communication for the encrypted messages remains the same as in Kantarcioglu et al.'s work (linear with the number of data items). Furthermore, we provide the security model in Universal Composability framework.