ALARM: Active LeArning of Rowhammer Mitigations
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 36 references that are in the map. First posted on arXiv 30 Nov 2022.
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4 of 36 references.
References · 4
- 2021Uncovering In-DRAM RowHammer Protection Mechanisms: A New Methodology, Custom RowHammer Patterns, and Implicationscited by 7
- 2021Prognosis: Closed-Box Analysis of Network Protocol Implementationscited by 7
- 2019CacheQuery: Learning Replacement Policies from Hardware Cachescited by 3
- 2018SoftMC: Practical DRAM Characterization Using an FPGA-Based Infrastructurecited by 1
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