Data Mining Over Encrypted Big Data Using Rings and Non-commutative Generalizations of Polly-Cracker Schemes
The City University of New York, USA
Date: 13 Jul 2017, Time: 15:00-16:00, Room: 26-00/332
In the first of part of my talk, I will talk about data-mining over encrypted big data. This part proposes ideas of using combinatorial algebra for Fully Homomorphic Encryption.
Homomorphic encryption is a form of encryption which allows various types of computations to be carried out on ciphertext and generate an encrypted result which, when decrypted, matches the result of operations performed on the plaintext. This is a desirable feature in modern communication system architectures. Homomorphic encryption would allow chaining together different services without exposing the data to each of those services. The homomorphic property of various cryptosystems can be used, in particular, to create private information retrieval schemes and enable widespread use of cloud computing by ensuring the confidentiality of processed data. In this talk, I will present an efficient Fully Homomorphic Encryption (FHE) scheme using non-commutative algebraic structure. I will also discuss applications that enables doing various machine learning and statistical analysis over encrypted big data. There has been some experiments carried out over medical data particularly. This is a joint work with V. Shpilrain
In the second part of my talk, I will talk about non-commutative generalizations of Polly-Cracker cryptosystems. Some variations of Polly-Cracker cryptosystems have been proposed as post-quantum resistant as well as fully homomorphic encryption, mainly by PolSys team. This part of my talk is a joint ongoing project with D. Savchuck and V. Shpilrain.
Fast(er) linear algebra on multivariate Hankel matrices
AROMATH, Inria Sophia Antipolis Mediterranee
Date: 17 Noe 2016, Time: 11:00-12:00, Room: 26-00/101
Symbolic Determinants support Numerical Methods
Johann Radon Institute for Computational and Applied Mathematics (RICAM), Linz Austria
Date: 8 Noe 2016, Time: 11:00-12:00, Room: 25-26/105