Collaborative filtering with privacy via factor analysis
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CRYPTO '97 Proceedings of the 17th Annual International Cryptology Conference on Advances in Cryptology
Practical Threshold RSA Signatures without a Trusted Dealer
EUROCRYPT '01 Proceedings of the International Conference on the Theory and Application of Cryptographic Techniques: Advances in Cryptology
Sharing Decryption in the Context of Voting or Lotteries
FC '00 Proceedings of the 4th International Conference on Financial Cryptography
PKC '01 Proceedings of the 4th International Workshop on Practice and Theory in Public Key Cryptography: Public Key Cryptography
Collaborative Filtering with Privacy
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
On the Privacy Preserving Properties of Random Data Perturbation Techniques
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Shilling recommender systems for fun and profit
Proceedings of the 13th international conference on World Wide Web
SVD-based collaborative filtering with privacy
Proceedings of the 2005 ACM symposium on Applied computing
Preventing shilling attacks in online recommender systems
Proceedings of the 7th annual ACM international workshop on Web information and data management
A privacy-preserving collaborative filtering scheme with two-way communication
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Secure two-party k-means clustering
Proceedings of the 14th ACM conference on Computer and communications security
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ARES '08 Proceedings of the 2008 Third International Conference on Availability, Reliability and Security
TrustWalker: a random walk model for combining trust-based and item-based recommendation
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Differentially private recommender systems: building privacy into the net
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
EUROCRYPT'91 Proceedings of the 10th annual international conference on Theory and application of cryptographic techniques
Public-key cryptosystems based on composite degree residuosity classes
EUROCRYPT'99 Proceedings of the 17th international conference on Theory and application of cryptographic techniques
Differential privacy: a survey of results
TAMC'08 Proceedings of the 5th international conference on Theory and applications of models of computation
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II
Efficient binary conversion for paillier encrypted values
EUROCRYPT'06 Proceedings of the 24th annual international conference on The Theory and Applications of Cryptographic Techniques
Applicability of recommender systems to medical surveillance systems
Proceedings of the second international workshop on Web science and information exchange in the medical web
Reliable medical recommendation systems with patient privacy
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
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One of the concerns patients have when confronted with a medical condition is which physician to trust. Any recommendation system that seeks to answer this question must ensure any sensitive medical information collected by the system is properly secured. In this paper we codify these privacy concerns in a privacy-friendly framework and present two architectures that realize it: the Secure Processing Architecture (SPA) and the Anonymous Contributions Architecture (ACA). In SPA, patients submit their ratings in a protected form without revealing any information about their data, and the computation of recommendations proceeds over the protected data using secure multi-party computation techniques. In ACA, patients submit their ratings in the clear, but no link between a submission and patient data can be made. We discuss various aspects of both architectures including techniques for ensuring reliability of computed recommendations and system performance, and provide their comparison.