ALARM: Active LeArning of Rowhammer Mitigations

11/30/2022

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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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ALARM: Active LeArning of Rowhammer Mitigations

Uncovering In-DRAM RowHammer Protection Mechanisms: A New Methodology, Custom RowHammer Patterns, and Implications

GhostKnight: Breaching Data Integrity via Speculative Execution

X-ray: Discovering DRAM Internal Structure and Error Characteristics by Issuing Memory Commands

Retrospective: Flipping Bits in Memory Without Accessing Them: An Experimental Study of DRAM Disturbance Errors

DRAMDig: A Knowledge-assisted Tool to Uncover DRAM Address Mapping

Towards the Avoidance of Counterfeit Memory: Identifying the DRAM Origin

Improvement in Retention Time of Capacitorless DRAM with Access Transistor

ALARM: Active LeArning of Rowhammer Mitigations

Related Research

Uncovering In-DRAM RowHammer Protection Mechanisms: A New Methodology, Custom RowHammer Patterns, and Implications

GhostKnight: Breaching Data Integrity via Speculative Execution

X-ray: Discovering DRAM Internal Structure and Error Characteristics by Issuing Memory Commands

Retrospective: Flipping Bits in Memory Without Accessing Them: An Experimental Study of DRAM Disturbance Errors

DRAMDig: A Knowledge-assisted Tool to Uncover DRAM Address Mapping

Towards the Avoidance of Counterfeit Memory: Identifying the DRAM Origin

Improvement in Retention Time of Capacitorless DRAM with Access Transistor