Speaker: Sebastian Mazza (Inst. 193-02)
Realtime rendering of volume data sets requires lots of processing power and, therefore, depends on the availability of powerful graphics hardware. Thin clients like tablets or smart phones often do not have enough memory and processing power for rendering big volume data sets. A possible solution for this problem is to render the images on remote systems and use the thin client only for displaying the rendered images. However, that would make it necessary to acquire and maintain a probably expensive server system.
Another option is to rent processing power only when required (e.g. from so-called cloud
providers). The issue with this approach is that the volume data is not longer under the control of the owner because it needs to be transferred to a server where access to the data can not be regulated by the owner any more. That means that everyone who has access to the server can use the data. This could be the owner of the server hardware, a system administrator or a hacker who has obtained an unauthorized access to the system. Therefore, cloud computing is not an option for many volume rendering tasks, at least not if sensitive data like CT or MRI scans of patients need to be processed.
Currently the cloud can only be used for storing sensitive volume data because they can be encrypted by a secure encryption like AES [2]. However, the goal of this work is to develop a volume rendering approach which allows the outsourcing of the whole volume rendering pipeline to untrusted third party servers, while preserving the same level of privacy as within a local volume rendering. This would make it possible to render sensitive volume data on untrusted hardware of cloud providers.
Zoom Meeting https://tuwien.zoom.us/j/98393883533?pwd=eVVhQ05PVjZiL292c2xhNVYvT0lqUT09
Meeting ID: 983 9388 3533
Password: 8t396a37