ALARM: Active LeArning of Rowhammer Mitigations

• URL: http://arxiv.org/abs/2211.16942v1
• Date: Wed, 30 Nov 2022 12:24:35 GMT
• Title: ALARM: Active LeArning of Rowhammer Mitigations
• Authors: Amir Naseredini, Martin Berger, Matteo Sammartino, Shale Xiong
• Abstract summary: Rowhammer is a serious security problem of contemporary dynamic random-access memory (DRAM) We present a tool, based on active learning, that automatically infers parameter of Rowhammer mitigations against synthetic models of modern DRAM.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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