EraseMe: A Defense Mechanism against Information Leakage exploiting GPU Memory

Graphics Processing Units (GPU) play a major role in speeding up computational tasks of the users, especially in applications such as high volume text and image processing. Recent works have demonstrated the security problems associated with GPU that do not erase the remnant data left behind by previous applications prior to OS context switching. In these attacks, adversaries are able to allocate their memory region on the same memory region used by previous applications and are able to steal their secrets. To overcome this problem, one needs to erase every modified memory page, and this process incurs very high latencies (order of several seconds to even minutes). In this work, we propose EraseMe, a lightweight, content-aware memory-cleansing framework that identifies and erases the sensitive memory pages left behind by victim applications. Our preliminary evaluation shows that EraseMe is able to increase the difficulty of image reconstruction by over 10× for the attacker.