Fortanix improves capabilities of runtime encryption to Python and R based applications for data analysis and machine learning

Fortanix Inc. announced this week that it has extended the capabilities of its initial Runtime Encryption Platform to secure Python- and R-based applications that have widespread use in the data science community. As a result, developers and data scientists can now train artificial intelligence (AI) and machine learning (ML) algorithms leveraging sensitive data as inputs without compromising on the confidentiality of the data.

Fortanix Runtime Encryption, leveraging Intel Software Guard Extensions Intel  SGX, enables secure exchange of data for the necessary training of machine learning models, as well as its secure execution inside SGX enclaves. Some of the most transformative benefits of AI can come from its application to industries such as healthcare, automotive and financial services, but one of its inhibitive factors has been lack of strong controls to protect personal sensitive and private datasets that are necessary inputs to train the models.

Runtime Encryption provides a security framework to ensure that the sensitive data remains confidential even when in use.

Fortanix Runtime Encryption now supports container-based Python applications as well as applications that are developed using R language. Python is a more full-fledged programming language, whereas R is popular in data science and statistical modeling with extensive use in healthcare and financial services. Runtime Encryption can protect the applications without requiring modifications.

“Runtime Encryption, using Intel SGX, delivers new levels of security for applications in the cloud, and protecting the confidentiality of sensitive data for AI apps is yet another exciting example,” said Ambuj Kumar, co-founder and CEO of Fortanix. “Runtime Encryption ensures confidentiality of data and secure execution enabling a new class of AI apps for healthcare, financial services and other sectors dealing with confidential information.”

“It is exciting to see how Fortanix continues to innovate and is helping to address the data privacy and security challenges of new workloads like AI,” said Rick Echevarria, Vice President, Software and Services Group and General Manager, Platforms Security Division at Intel. “By utilizing hardware-secured technologies, such as Intel Software Guard Extensions (Intel SGX), mutual customers can enhance protection of their sensitive data and algorithms.”

“GeneTank is pleased to collaborate with Fortanix to enable secure computation for Bioinformatics,” said Anne Kim, CEO, GeneTank. “Fortanix Runtime Encryption supports our vision of enabling a secure and transparent marketplace for genetic and health algorithms and AI services.”

“iExec sees tremendous potential in leveraging Blockchain to increase the effectiveness of AI,” said Lei Zhang, Security R&D manager, iExec. “We are very pleased to collaborate with Fortanix to secure Blockchain-based decentralized computing. Fortanix Runtime Encryption can ensure that an iExec DApp built using R can be deployed with a privacy token that remains completely protected.”

Last month, Fortanix announced that it has integrated its Self-Defending Key Management Service (SDKMS) with technology partners to offer next-generation hardware security module (NGHSM) solutions for access management, data-at-rest encryption, payments, and Internet of Things (IoT).

Fortanix’s SDKMS leverages Runtime Encryption and Intel SGX to deliver security for encryption keys and cryptographic services with software-defined simplicity. The solution offers flexible consumption models; a hardened appliance; and a SaaS service Equinix SmartKey, powered by Fortanix. The solution is architected to enable easy integration for new modern cloud applications, as well as existing applications with support for both RESTful APIs and traditional cryptographic interfaces including PKCS#11, JCE and CNG.

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