Machine learning is one of the hottest disciplines in computer science today. So hot, in fact, that cloud providers are doing a good and rapidly growing business in machine-learning-as-a-service (MLaaS).
But these services come with a caveat: all the training data must be revealed to the service operator. Even if the service operator does not intentionally access the data, someone with nefarious motives may. Or their may be legal reasons to preserve privacy, such as with health data.
In a recent paper, Chiron: Privacy-preserving Machine Learning as a Service Tyler Hunt, of the University of Texas, and others, presents a system that preserves privacy while enabling the use of cloud MLaaS.
Read more about how we might be able to use machine-learning-as-service while protecting privacy on ZDNet.