Lune

ASPLOS2026Top-tier venue

APT: Securing Against DRAM Read Disturbance via Adaptive Probabilistic In-DRAM Trackers

Runjin Wu, Meng Zhang, You Zhou, Changsheng Xie, Fei Wu

2026Year
2Citations
2Top-tier citations

Abstract

With exacerbated DRAM read disturbance, transparent in-DRAM defenses require space (to track the aggressor rows) and time (to perform more mitigations). To reduce storage overhead, recent works have developed probabilistic row-sampling techniques with several entries. To address the time issue, these techniques employ Refresh Management (RFM) commands introduced in DDR5. However, probabilistic defenses with RFM face two critical challenges: (i) fixed-probability sampling under dynamic activation patterns can cause row-sampling misses, allowing attacks to evade mitigation, and (ii) RFM causes timing variations that can be exploited for side and covert channels to leak sensitive information. The goal of this paper is to design a low-cost and secure in-DRAM defense that overcomes these challenges.

Ask about this paper

Ask your agent about it.

Lune has read the top-tier papers around this one, so every answer names the papers it rests on.

Questions to start from

Your agent calls

Lunesearch_papers

Ask in Lune

Free to start. No credit card required.

lune papers get f864d5df-1b83-406a-b29e-6b321408f91a

Cited by top-tier papers2

Ask how each one uses it

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines