Des chercheurs exploitent les empreintes digitales du GPU pour suivre les utilisateurs en ligne
What would happen if someone were to precisely explore the differences in GPUs and use those differences to identify online users by those characteristics? This is exactly what researchers that created DrawnApart thought of. Using WebGL, they run a GPU workload that identifies more than 176 measurements across 16 data collection places. This is done using vertex operations in GLSL (OpenGL Shading Language), where workloads are prevented from random distribution on the network of processing units. DrawnApart can measure and record the time to complete vertex renders, record the exact route that the rendering took, handle stall functions, et beaucoup plus. This enables the framework to give off unique combinations of data turned into fingerprints of GPUs, which can be exploited online. Below you can see the data trace recording of two GPUs (same models) showing variations.
Khronos Group, creators of WebGL API, has set up a working group to handle this situation and prevent the API from giving off too much information to track users online. If you wish to learn more about this technique, you can read it on ArXiv here.