A systematic and comprehensive review of security and privacy-preserving challenges in e-
health solutions indicates various privacy preserving approaches to ensure privacy and …

Cloud based healthcare computing have changed the face of healthcare in many ways. The
main advantages of cloud computing in healthcare are scalability of the required service and …

The proliferation of various mobile devices equipped with cameras results in an exponential
growth of the amount of images. Recent advances in the deep learning with convolutional …

The explosive growth of biometrics use (eg, in surveillance) poses a persistent challenge to
keep biometric data private without sacrificing the apps' functionality. We consider private …

To solve the privacy image problem stored in cloud, we propose a compressive sensing
(CS) based image compression, authentication, encryption algorithm in cloud, which can …

The widespread application of biometric recognition has emerged solid protection on the
privacy of biometric templates. Non-invertible transformations such as random projections …

Biometric verification systems have become prevalent in the modern world with the wide
usage of smartphones. These systems heavily rely on storing the sensitive biometric data on …

Cloud-assisted biometric identification can benefit data owners with limited resources by
offloading their storage and identification tasks to cloud servers with abundant resources …

Mobile crowdsensing (MCS) is widely applied in large-scale distributed networks for
collecting sensing data from workers. In an MCS system, workers are recruited to complete …

Biometric identification has developed rapidly in recent years because of its convenience
and reliability. Due to the sensitivity of biometric data, many privacy-preserving biometric …