一句话：Rubix 通过加密地址随机化缓存行到 DRAM 行的映射以减少热点行，将安全 Rowhammer 缓解开销降至 1%–3%。
现代 Rowhammer 缓解多采用 victim refresh，但 Half-Double 等攻击可绕过；AQUA、SRS、Blockhammer 等对 aggressor 采取行动的安全方案在低阈值下产生 15%–600% 的 slowdown。Rubix 观察到，内存映射为提升 row-buffer 命中率，将空间邻近的缓存行放入同一 DRAM 行，导致正常应用出现大量热点行。Rubix 使用加密地址随机化 line-to-row 映射，打破空间相关性，将热点行概率降低 2–3 个数量级，并以 1–4 行分组随机化保留行缓冲命中。Rubix-D 动态改变映射，进一步减少热点行并阻止攻击者学习行的空间邻域。评估表明，Rubix 将 AQUA、SRS、Blockhammer 的 slowdown 分别从 15%、60%、600% 降至 1%、2%、3%，额外存储不足 1KB。
Modern systems mitigate Rowhammer using victim refresh, which refreshes neighbours of an aggressor row when it encounters a specified number of activations. Unfortunately, complex attack patterns like Half-Double break victim-refresh, rendering current systems vulnerable. Instead, recently proposed secure Rowhammer mitigations perform mitigative action on the aggressor rather than the victims. Such schemes employ mitigative actions such as row-migration or access-control and include AQUA, SRS, and Blockhammer. While these schemes incur only modest slowdowns at Rowhammer thresholds of few thousand, they incur prohibitive slowdowns (15%-600%) for lower thresholds that are likely in the near future. The goal of our paper is to make secure Rowhammer mitigations practical at such low thresholds. Our paper provides the key insights that benign application encounter thousands of hot rows (receiving more activations than the threshold) due to the memory mapping, which places spatially proximate lines in the same row to maximize row-buffer hitrate. Unfortunately, this causes row to receive activations for many frequently used lines. We propose Rubix, which breaks the spatial correlation in the line-to-row mapping by using an encrypted address to access the memory, reducing the likelihood of hot rows by 2 to 3 orders of magnitude. To aid row-buffer hits, Rubix randomizes a group of 1-4 lines. We also propose Rubix-D, which dynamically changes the line-to-row mapping. Rubix-D minimizes hot-rows and makes it much harder for an adversary to learn the spatial neighbourhood of a row. Rubix reduces the slowdown of AQUA (from 15% to 1%), SRS (from 60% to 2%), and Blockhammer (from 600% to 3%) while incurring a storage of less than 1 Kilobyte.
@inproceedings{SaxenaMQ24,
title = {Rubix: Reducing the Overhead of Secure Rowhammer Mitigations via Randomized Line-to-Row Mapping},
author = {Anish Saxena and Saurav Mathur and Moinuddin Qureshi},
booktitle = {ASPLOS},
year = {2024},
doi = {10.1145/3620665.3640404}
}