SYSTEMS AND METHODS FOR SECURELY TRAINING A DECISION TREE

    公开(公告)号:US20230006980A1

    公开(公告)日:2023-01-05

    申请号:US17939797

    申请日:2022-09-07

    申请人: TripleBlind, Inc.

    摘要: A system and method for training a decision tree are disclosed. A method includes publishing, by a first party, a first set of nominated cut-off values at a current node of a decision tree to be trained, computing a first respective impurity value for the first set of nominated cut-off values at the current node, creating first respective n shares of the first respective impurity value, transmitting, from the first party and so a second party, one of the first respective n shares of the first respective impurity value, receiving from the second party one of a second respective n shares of the second respective impurity value, adding a group of impurity values to yield a combined impurity value based on the one of the first respective n shares and the one of the second respective n shares and determining, based on the combined impurity value, a best threshold.

    Systems and methods for providing a marketplace where data and algorithms can be chosen and interact via encryption

    公开(公告)号:US11363002B2

    公开(公告)日:2022-06-14

    申请号:US16828420

    申请日:2020-03-24

    申请人: TripleBlind, Inc.

    摘要: A method includes receiving, on a computer-implemented system and from user, an identification of data and an identification of an algorithm and, based on a user interaction with the computer-implemented system comprising a one-click interaction or a two-click interaction. Without further user input, the method includes dividing the data into a data first subset and a data second subset, dividing the algorithm (or a Boolean logic gate representation of the algorithm) into an algorithm first subset and an algorithm second subset, running, on the computer-implemented system at a first location, the data first subset with the algorithm first subset to yield a first partial result, running, on the computer-implemented system at a second location separate from the first location, the data second subset with the algorithm second subset to yield a second partial result and outputting a combined result based on the first partial result and the second partial result.

    Systems and methods for encrypting data and algorithms

    公开(公告)号:US11582203B2

    公开(公告)日:2023-02-14

    申请号:US16828085

    申请日:2020-03-24

    申请人: TripleBlind, Inc.

    摘要: Systems, methods, and computer-readable media for achieving privacy for both data and an algorithm that operates on the data. A system can involve receiving an algorithm from an algorithm provider and receiving data from a data provider, dividing the algorithm into a first algorithm subset and a second algorithm subset and dividing the data into a first data subset and a second data subset, sending the first algorithm subset and the first data subset to the algorithm provider and sending the second algorithm subset and the second data subset to the data provider, receiving a first partial result from the algorithm provider based on the first algorithm subset and first data subset and receiving a second partial result from the data provider based on the second algorithm subset and the second data subset, and determining a combined result based on the first partial result and the second partial result.

    SYSTEMS AND METHODS FOR TREE-BASED MODEL INFERENCE USING MULTI-PARTY COMPUTATION

    公开(公告)号:US20230006978A1

    公开(公告)日:2023-01-05

    申请号:US17939285

    申请日:2022-09-07

    申请人: TripleBlind, Inc.

    摘要: A system and method for securely computing an inference of two types of tree-based models, namely XGBoost and Random Forest, using secure multi-party computation protocol. The method includes computing a respective comparison result of each respective node of a plurality of nodes in a tree classifier. Each node has a respective threshold value. The respective comparison result is based on respective data associated with a data owner device being applied to a respective node having the respective threshold value. The method includes computing, based on the respective comparison result, a leaf value associated with the tree classifier, generating a share of the leaf value and transmitting, to the data owner device, a share of the leaf value. The data owner device computes, using a secure multi-party computation and between the model owner device and the data owner device, the leaf value for the respective data of the data owner.