STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Communication preserving protocols for secure function evaluation
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Mix and Match: Secure Function Evaluation via Ciphertexts
ASIACRYPT '00 Proceedings of the 6th International Conference on the Theory and Application of Cryptology and Information Security: Advances in Cryptology
Secure and private sequence comparisons
Proceedings of the 2003 ACM workshop on Privacy in the electronic society
Secure function evaluation with ordered binary decision diagrams
Proceedings of the 13th ACM conference on Computer and communications security
Privacy preserving error resilient dna searching through oblivious automata
Proceedings of the 14th ACM conference on Computer and communications security
Protocols for secure computations
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Towards Practical Privacy for Genomic Computation
SP '08 Proceedings of the 2008 IEEE Symposium on Security and Privacy
Cryptocomputing with rationals
FC'02 Proceedings of the 6th international conference on Financial cryptography
Efficient and secure comparison for on-line auctions
ACISP'07 Proceedings of the 12th Australasian conference on Information security and privacy
Private predictions on hidden Markov models
Artificial Intelligence Review
Secure computation with fixed-point numbers
FC'10 Proceedings of the 14th international conference on Financial Cryptography and Data Security
A Framework for Secure Speech Recognition
IEEE Transactions on Audio, Speech, and Language Processing
Processing encrypted floating point signals
Proceedings of the thirteenth ACM multimedia workshop on Multimedia and security
Secure computations on non-integer values with applications to privacy-preserving sequence analysis
Information Security Tech. Report
Secure genomic testing with size- and position-hiding private substring matching
Proceedings of the 12th ACM workshop on Workshop on privacy in the electronic society
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In this paper we show how privacy of genomic sequences can be protected while they are analyzed using Hidden Markov Models (HMM), which is commonly done in bioinformatics to detect certain non-beneficial patterns in the genome. Besides offering strong privacy guarantees, our solution also allows protecting the intellectual property of the parties involved, which makes the solution viable for implementation of secure bioinformatics services. In particular, we show how two mutually mistrusting parties can obliviously run the forward algorithm in a setup where one party knows a HMM and another party knows a genomic string; while the parties learn whether the model fits the genome, they neither have to disclose the parameterization of the model nor the sequence to each other. Despite the huge number of arithmetic operations required to solve the problem, we experimentally show that HMMs with sizes of practical importance can obliviously be evaluated using computational resources typically found in medical laboratories. As a central technical contribution, we give improved protocols for secure and numerically stable computations on non-integer values.