In one embodiment, a set of feature vectors can be derived from any biometric data, and
then using a deep neural network (“DNN”) on those one-way homomorphic encryp tions (ie …

Provided are methods and systems for performing a secure machine learning analysis over
an instance of data. An example method includes acquiring, by a client, an homo morphic …

(57) ABSTRACT A set of distance measurable encrypted feature vectors can be derived from
any biometric data and/or physical or logical user behavioral data, and then using an …

Provided are methods and systems for performing a secure analytic over a data source. An
example method includes acquiring, by a client, an analytic, at least one analytic parameter …

Multiple data sources encrypt data using encryption key data received from a first system; a
second system does not have access to the encryption key data. The second system …

(57) ABSTRACT A set of distance measurable encrypted feature vectors can be derived from
any biometric data and/or physical or logical user behavioral data, and then using an …

In one embodiment, a set of feature vectors can be derived from any biometric data, and
then using a deep neural network (“DNN”) on those one-way homomorphic encryp tions (ie …

Implementations of the present disclosure include receiving, from a first account, a digitally
signed copy of a commitment value of a first amount of a transaction amount generated …

An example operation may include one or more of connect ing, by an identity server, to a
blockchain configured to store an identity trait of a user, retrieving, by an identity server, the …

Systems and methods of authorizing access to access-con trolled environments are
provided. In one example, a method includes receiving, passively by a computing device …