NYC FinTech Innovation Lab Selects Inpher for 2019 Program
-Inpher VP of Business Development, Kevin McCarthy, presents Secret Computing Inpher was selected among a field of hundreds…
Why Encryption of Corp Data is a Powerful but Underutilized Tool
-In her article Why Don’t Companies Just Encrypt All Their Data? Sara Castellanos details the traditional trade-offs that enterprises make…
Partnering for Privacy-Preserving Predictive Maintenance
-From left to right: Jonathan Rouach- CEO, QEDit; Jean-Yves Plu- VP, Thales; Jordan Brandt- CEO,…
Playing with Encrypted Data – Without Seeing It
-As David Morris writes in the Financial News Fintech Files, “With the GDPR deadline bearing down on European financial…
Securing Autonomous Fleets with Global-Trained Localized Brains
-The value of connected everything will be derived from unprecedented data sharing, none the more so than with…
Deep Learning in Finance
-The Deep Learning in Finance Summit hosted by Re-Work on March 15-16 in London brings together experts and practitioners in…
Financial Cryptography 2018
-This year in Curaçao, the Twenty-Second International Conference for Financial Cryptography will convene with salient topics in secure…
Inpher presents an Innovative solution for AML/CFT at the ACPR Banque de France TechSprint
This article was originally published on AWS blogs by Conor Moran, Sr. Director, Business Development, Inpher.
AWS users occasionally need to perform analysis on data sources containing private or sensitive inputs. Inpher’s XOR Secret Computing Platform, available in AWS Marketplace, enables data scientists to train and run machine learning models while maintaining data privacy and without trading utility. Data analysis and machine learning performed by XOR can improve model performance with mathematically guaranteed data privacy while ensuring the data never leaves the data source.
Inpher’s Research on Privacy-Preserving Machine Learning Published in Two Premier Conferences
This article was originally published on AWS blogs by Conor Moran, Sr. Director, Business Development, Inpher.
AWS users occasionally need to perform analysis on data sources containing private or sensitive inputs. Inpher’s XOR Secret Computing Platform, available in AWS Marketplace, enables data scientists to train and run machine learning models while maintaining data privacy and without trading utility. Data analysis and machine learning performed by XOR can improve model performance with mathematically guaranteed data privacy while ensuring the data never leaves the data source.
How DataCo is Reinventing Data Partnerships by Putting Privacy-Enhancing Technologies to Work
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Inpher Announces Strategic Partnership with In-Q-Tel
This article was originally published on AWS blogs by Conor Moran, Sr. Director, Business Development, Inpher.
AWS users occasionally need to perform analysis on data sources containing private or sensitive inputs. Inpher’s XOR Secret Computing Platform, available in AWS Marketplace, enables data scientists to train and run machine learning models while maintaining data privacy and without trading utility. Data analysis and machine learning performed by XOR can improve model performance with mathematically guaranteed data privacy while ensuring the data never leaves the data source.
