Graphics processing units (GPUs) are important components of modern computing devices for not only graphics rendering, but also efficient parallel computations. However, their security problems are ignored despite their importance and popularity. In this paper, we first perform an in-depth security analysis on GPUs to detect security vulnerabilities. We observe that contemporary, widely-used GPUs, both NVIDIA's and AMD's, do not initialize newly allocated GPU memory pages which may contain sensitive user data. By exploiting such vulnerabilities, we propose attack methods for revealing a victim program's data kept in GPU memory both during its execution and right after its termination. We further show the high applicability of the proposed attacks by applying them to the Chromium and Firefox web browsers which use GPUs for accelerating webpage rendering. We detect that both browsers leave rendered webpage textures in GPU memory, so that we can infer which web pages a victim user has visited by analyzing the remaining textures. The accuracy of our advanced inference attack that uses both pixel sequence matching and RGB histogram matching is up to 95.4%.
|Title of host publication||Proceedings - IEEE Symposium on Security and Privacy|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||15|
|Publication status||Published - 2014 Nov 13|
|Event||35th IEEE Symposium on Security and Privacy, SP 2014 - San Jose, United States|
Duration: 2014 May 18 → 2014 May 21
|Name||Proceedings - IEEE Symposium on Security and Privacy|
|Conference||35th IEEE Symposium on Security and Privacy, SP 2014|
|Period||14/5/18 → 14/5/21|
Bibliographical notePublisher Copyright:
© 2014 IEEE.
All Science Journal Classification (ASJC) codes
- Safety, Risk, Reliability and Quality
- Computer Networks and Communications