论文标题
警报：主动学习Rowhammer缓解措施
ALARM: Active LeArning of Rowhammer Mitigations
论文作者
论文摘要
Rowhammer是当代动态随机访问记忆（DRAM）的严重安全问题，其中读取或写作可以翻转其他位。 DRAM制造商增加了缓解措施，但不要透露细节，因此很难评估其功效。我们提出了一种基于主动学习的工具，该工具会自动进化针对现代DRAM的合成模型的Rowhammer缓解参数。
Rowhammer is a serious security problem of contemporary dynamic random-access memory (DRAM) where reads or writes of bits can flip other bits. DRAM manufacturers add mitigations, but don't disclose details, making it difficult for customers to evaluate their efficacy. We present a tool, based on active learning, that automatically infers parameter of Rowhammer mitigations against synthetic models of modern DRAM.
