IAPP Canada Privacy Symposium 2013
There are often privacy and confidentiality concerns with putting sensitive personal information about employees or customers in the cloud, and the same concerns surround large-scale analytics in the cloud. Learn how secure analytics work, including examples of their application in the healthcare context. We’ll explore the processes involved in secure computation, including the use of homomorphic encryption. Example scenarios where secure computation in the cloud can be used include: a health researcher sharing data with the broader research community by posting the encrypted data online and still permitting analytics on that data; a financial services company that wants to take advantage of the elastic computing capacity in the cloud without having to trust the cloud provider with its sensitive data; and a wellness company collecting PI directly from consumers either online or through wearable devices, and then performing analytics on the data for benchmarking purposes, without knowing the exact values collected from the consumers. Join us for this overview of secure computation, how it protects privacy and confidentiality and its limitations, and hear some real-world examples of how it has been used in the healthcare sector. These examples include public health surveillance, the sharing of clinical research data and securely tracking individuals as they visit multiple care facilities.