Abstract Human activity recognition (HAR) generates a massive amount of the dataset from Internet Things (IoT) devices, to enable multiple data providers jointly produce predictive models for medical diagnosis. That accuracy is greatly improved when trained on large number datasets these untrusted cloud server very significant and raises privacy concerns. With migration deep neural network (DNN...

In emerging information networks, having a privacy preserving index (or PPI) is critically important for locating information of interest for data sharing across autonomous providers while preserving privacy. An understudied problem for PPI techniques is how to provide controllable privacy preservation, given the innate difference of privacy concerns regarding different data owners. In this pap...

In information sharing networks, having a privacy preserving index (or PPI) is critically important for providing efficient search on access controlled content across distributed providers while preserving privacy. An understudied problem for PPI techniques is how to provide controllable privacy preservation, given the innate difference of privacy of the different content and providers. In this...

Preserving Privacy is crucial in distributed environments wherein data mining becomes a collaborative task among participants. Critical applications in distributed environment demand higher level of privacy with lesser overheads. Solutions proposed on the lines of cryptography provide higher level of privacy but poor scalability due to higher overheads. Further, existing cryptography based solu...