The Potential for Machine Learning Analysis over Encrypted Data in Cloud-based Clinical Decision Support – Background and Review

@inproceedings{Basilakis2015ThePF,
  title={The Potential for Machine Learning Analysis over Encrypted Data in Cloud-based Clinical Decision Support – Background and Review},
  author={Jim Basilakis and Bahman Javadi and Anthony Maeder},
  year={2015}
}
In an effort to reduce the risk of sensitive data exposure in untrusted networks such as the public cloud, increasing attention has recently been given to encryption schemes that allow specific computations to occur on encrypted data, without the need for decryption. This relies on the fact that some encryption algorithms display the property of homomorphism, which allows them to manipulate data in a meaningful way while still in encrypted form. Such a framework would find particular relevance… CONTINUE READING