Sensors and in particular cameras have found their way into many parts of our daily lives. While monitoring public places is still a common use case for camera systems, applications in private environments are emerging. The ever growing number of cameras raises important questions concerning security and privacy. “Our approach to tackle these questions is to protect all sensitive data before it leaves the camera,” explains Bernhard Rinner. “We exploit the available computing resources of modern camera systems for onboard privacy protection and data security and do not rely on pure software solutions. We have successfully demonstrated this approach on several prototypes.”

TrustEYE.M4 platform for secure and privacy-aware visual sensor networks.

System-on-chip prototype with onboard security functionality. Key generation based on physical unclonable functions, sensed data attestation, and secure boot of the sensor controller are implemented on a Xilinx Zynq7010.

Privacy protection is achieved by intentionally distorting sensitive regions of the captured images. In a first approach we have developed so-called cartooning privacy filters which preserve privacy while ensuring a minimum reduction of the image fidelity and run onboard of our TrustEYE platform.

Visualisation of hopping blur filtering. The face region is divided into sub-regions and each sub-region is convolved with a hopping Gaussian mixture model kernel based on random parameters.