Category: Confidential Computing

Artificial Intelligence

AI in Healthcare Security

HUB Security’s hardware solution allows a safe environment for machine learning and artificial intelligence processes to take place, while any concern for unwanted visibility between different models. By using Confidential Computing methods we allow for effective collaborative machine learning to take place, thus enabling previously unattainable ventures, in a secure environment.

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Confidential computing diagram
Artificial Intelligence

Cutting Edge

For the experienced reader, edge computing should not be too hard to comprehend. In July 1969, Apollo 11 landed on the moon, in large part

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Valerii Babushkin
Artificial Intelligence

AI & Data Privacy with Valerii Babushkin

Towards our online summit on June 10th, AI and Data Privacy we set down for an interview with Valerii Babushkin, WhatsApp User Data Privacy Tech Lead, who will be joining the event.

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Security threats facing AI and ML
Artificial Intelligence

Top 5 Security Threats Facing Artificial Intelligence and Machine Learning

An emerging space within AI is the need to share and access more big data from semi trusting parties in order to achieve better models and insights. A good example is multiple healthcare providers sharing images and their interpretation in order to create an AI model to detect anomalies on its own. The more images the better algorithm. This scenario requires the model to access data from all healthcare providers, but assure that images cannot be accessed by each individual healthcare provider to another.

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