TY - GEN
T1 - Secure computation of hidden markov models
AU - Aliasgari, Mehrdad
AU - Blanton, Marina
PY - 2013
Y1 - 2013
N2 - Hidden Markov Model (HMM) is a popular statistical tool with a large number of applications in pattern recognition. In some of such applications, including speaker recognition in particular, the computation involves personal data that can identify individuals and must be protected. For that reason, we develop privacypreserving techniques for HMM and Gaussian mixture model (GMM) computation suitable for use in speaker recognition and other applications. Unlike prior work, our solution uses floating point arithmetic, which allows us to simultaneously achieve high accuracy, provable security guarantees, and reasonable performance. We develop techniques for both two-party HMM and GMM computation based on threshold homomorphic encryption and multi-party computation based on threshold linear secret sharing, which are suitable for secure collaborative computation as well as secure outsourcing.
AB - Hidden Markov Model (HMM) is a popular statistical tool with a large number of applications in pattern recognition. In some of such applications, including speaker recognition in particular, the computation involves personal data that can identify individuals and must be protected. For that reason, we develop privacypreserving techniques for HMM and Gaussian mixture model (GMM) computation suitable for use in speaker recognition and other applications. Unlike prior work, our solution uses floating point arithmetic, which allows us to simultaneously achieve high accuracy, provable security guarantees, and reasonable performance. We develop techniques for both two-party HMM and GMM computation based on threshold homomorphic encryption and multi-party computation based on threshold linear secret sharing, which are suitable for secure collaborative computation as well as secure outsourcing.
KW - Floating point
KW - Gaussian mixture models
KW - Hidden markov models
KW - Secure computation
UR - https://www.scopus.com/pages/publications/84887790712
M3 - Conference contribution
AN - SCOPUS:84887790712
SN - 9789898565730
T3 - ICETE 2013 - 10th International Joint Conference on E-Business and Telecommunications; SECRYPT 2013 - 10th International Conference on Security and Cryptography, Proceedings
SP - 242
EP - 253
BT - ICETE 2013 - 10th International Joint Conference on E-Business and Telecommunications; SECRYPT 2013 - 10th International Conference on Security and Cryptography, Proceedings
T2 - 10th International Conference on Security and Cryptography, SECRYPT 2013 - Part of 10th International Joint Conference on E-Business and Telecommunications, ICETE 2013
Y2 - 29 July 2013 through 31 July 2013
ER -