Privacy-preserving ridge regression on hundreds of millions of records

2020-02-17 21:05

privacypreserving linear regression protocols [21, 65 either dont use formal threat models, or leak additional information beyond the result of the computation.May 22, 2013 Abstract: Ridge regression is an algorithm that takes as input a large number of data points and finds the bestfit linear curve through these points. The algorithm is a building block for many machinelearning operations. We present a system for privacypreserving ridge regression. privacy-preserving ridge regression on hundreds of millions of records

In this talk we present a system in which ridge regression (that includes linear regression) is carried out in a privacy preserving way because the user data stays encrypted all the time. Ridge regression is an algorithm that takes as input a large number of data points

on Hundreds of Millions of Records Valeria Nikolaenko, Dan Boneh Udi Weinsberg, Stratis Ioannidis Stanford Marc Joye, Nina Taft CiteSeerX Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): AbstractRidge regression is an algorithm that takes as input a large number of data points and finds the bestfit linear curve through these points. The algorithm is a building block for many machinelearning operations. We present a system for privacypreserving ridge regression.privacy-preserving ridge regression on hundreds of millions of records privacypreserving ridge regression that uses both homomorphic encryption and Yao garbled circuits. We separate the regression algorithm into two phases, presented in detail in Section IV. Users submit their data encrypted under a linearly homomorphic encryption system such as Paillier [4 or Regev [5. The Evaluator uses the linear homomorphism

Privacy-preserving ridge regression on hundreds of millions of records free

We present a system for privacypreserving Ridge regression is an algorithm that takes as input a large number of data points and finds the bestfit linear curve through these points. The algorithm is a building block for many machinelearning operations. privacy-preserving ridge regression on hundreds of millions of records . Built a system to compute ridge regression preserving privacy ( nd best t curve for a collection of encrypted data points). . Archieved excelent scalability in the number of users (1, 000, 000 users). . Showed good performance on real datasets. I Challenges: . Method should be How can the answer be improved? Researchers have proposed privacy preserving ridge regression systems with the help of a cryptographic service provider [60, 34, 32, 33. While the authors in [33 use a hybrid multiparty

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