A Lightweight Isolation Mechanism for Secure Branch Predictors
Lutan Zhao, Peinan Li, Rui Hou, Michael Huang, Jiazhen Li, Lixin Zhang, Xuehai Qian, Dan Meng
Abstract
Recently exposed vulnerabilities reveal that branch predictors shared by different processes leave the attackers with the opportunities for malicious training and perception. Instead of flush-based or physical isolation of hardware resources, we want to achieve isolation of the content in these hardware tables with some lightweight processing using randomization as follows. (1) Content encoding. We propose to use hardware-based thread-private random numbers to encode the contents of the branch predictor tables. It achieves a similar effect of logical isolation but adds little in terms of space or time overheads. (2) Index encoding. We propose a randomized index mechanism of the branch predictor. This disrupts the correspondence between the branch instruction address and the branch predictor entry, thus increases the noise for malicious perception attacks. Our analyses using an FPGA-based RISC-V processor prototype and additional auxiliary simulations suggest that the proposed mechanisms incur a very small performance cost while providing strong protection.