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.”
The key idea is to “protect” access to the image sensor and encapsulate dedicated security and privacy functionality in a TrustEYE—a secure sensing unit embedded on the smart camera. The TrustEYE has exclusive access to the image sensor’s raw data. It separates sensitive from non-sensitive data by applying dedicated image analysis and ensures that only non-sensitive data is made available to the camera host system. “In another prototype, we use modern hybrid ARM/FPGA system on chip solutions to provide security and high speed image analysis functions,” Ihtesham Haider points out. “We exploit inherent hardware properties in the form of physical unclonable functions to realize high levels of security without requiring additional specialized hardware for cryptographic functions.”
Privacy protection is achieved by intentionally distorting sensitive regions of the captured images. “We have developed so-called cartooning privacy filters which preserve privacy while ensuring a minimum reduction of the image fidelity,” concludes Adam Erdelyi, who is currently working towards completing his PhD thesis.
A. Erdelyi, T. Winkler, and B. Rinner. Privacy Protection vs. Utility in Visual Data: An Objective Evaluation Framework. Multimedia Tools and Applications, Springer, 2018.
I. Haider and B. Rinner. Private Space Monitoring with SoC-based Smart Cameras. In Proc. IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS 2017), Olando, FL, USA. October 2017.
I. Haider, M. Hoeberl, and B. Rinner. Trusted Sensors for Participatory Sensing and IoT Applications based on Physically Unclonable Functions. In Proc. International Workshop IoT Privacy, Trust, and Security, 2016.
T. Winkler and B. Rinner. Security and Privacy Protection in Visual Sensor Networks: A Survey. ACM Computing Surveys, 2014.
A. Erdelyi, T. Barat, P. Valet, T. Winkler, and B. Rinner. Adaptive Cartooning for Privacy Protection in Camera Networks. In Proc. IEEE International Conference Advanced Video and Signal-Based Surveillance, 2014.