Knowledge Base

The Analytics and AI Challenge in Confidential Computing

Enclave innovation protects data from attack and unauthorized access, but it also presents immense challenges and obstacles to performing analytics and machine learning within and across teams. The inability to securely share data or analyze data that is owned by multiple parties has resulted in organizations having to restrict data access, eliminate data sets or …

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How to Defend Against Side-Channel Attacks on SGX

Our last blog post explained the concept of secure enclaves. In this blog post, we will specifically focus on hardware enclaves and discuss just how secure they are.  Introduction But first, a refresher on hardware enclaves for our new readers. Hardware enclaves provide an isolated environment for code and data within an untrusted machine, where …

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What are Secure Enclaves?

Some of the biggest barriers to cloud adoption are concerns about security, data loss/ leakage, and the associated legal and regulatory concerns with storing and processing data off-premises1. Several cloud data breach incidents in recent years indicate that these concerns are warranted as a result of constant insider and outsider threats. The challenge with Infrastructure …

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Federated Learning vs. Secure Collaborative Learning

Federated Learning vs. Secure Collaborative Learning

New techniques in analytics and machine learning offer the ability to process ever-increasing amounts of data, but access to such data has lagged far behind the technological advances in data processing. High-value data is often split across multiple organizations and access to it is encumbered by business competition and regulatory constraints. For example, banks wish …

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Secure computation: Homomorphic encryption or hardware enclaves

Secure computation: Homomorphic encryption or hardware enclaves?

Secure computation has become increasingly popular for protecting the privacy and integrity of data during computation. It offers two tremendous advantages: “encryption in use” in addition to the already existing “encryption at rest” and “encryption in transit”, and enabling different parties to collaborate and gain insights from their aggregate data, without sharing their data with …

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