Sunny Kang, Sr. Privacy Counsel and Head of Policy at Inpher, published in Just Security
-Don’t Blame Privacy for Big Tech’s Monopoly on Information As the prospect of antitrust charges against Big Tech…
A Call to Action: The Regulator’s Role in Supporting Privacy-Enhancing Technologies for Data-Driven Financial Crime Investigations
-Combating financial crimes and protecting privacy are equally critical goals in modern society. Financial crimes, when left undetected, can…
Cofounder & CTO Dr. Dimitar Jetchev Featured on the Frontpage of Forbes Bulgaria
-SOFIA, BULGARIA – Inpher Cofounder & CTO Dr. Dimitar Jetchev was recently featured on the frontpage of Forbes Bulgaria.…
Inpher’s Privacy-Preserving Cross-Border Analytics Case Study Published in Global FFIS Report
-LONDON, UK — As part of the technology working group on ‘The Role of Privacy Preserving Data Analytics in…
Director of Security Innovation Mariya Georgieva presents at ETSI Security Week
-Our Director of Security Innovation, Dr. Mariya Georgieva, was invited to present on fully homomorphic encryption (FHE) at this…
Inpher CEO Jordan Brandt interviewed on C-Suite Radio with Jeffrey Hayzlett
-Our CEO, Jordan Brandt, recently joined Jeffrey Hayzlett on C-Suite Radio to discuss how data privacy and AI are…
Inpher named in the 2020 Gartner Emerging Technologies: Homomorphic Encryption for Data Sharing With Privacy Report
-Inpher was recognized in an April 2020 report titled Emerging Technologies: Homomorphic Encryption for Data Sharing With Privacy, written…
Fighting the Fraud Surge in the COVID-19 Crisis
-As a result of the confusion and vulnerability that has arisen in the wake of the COVID-19 outbreak, there…
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
[spb_text_block animation=”none” animation_delay=”0″ simplified_controls=”yes” custom_css_percentage=”no” padding_vertical=”0″…
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.
