Probabilistic Tracker Management Policies for Low-Cost and Scalable Rowhammer Mitigation

TL;DR

This paper introduces PROTEAS, a probabilistic management policy for low-cost DRAM Rowhammer mitigation, significantly improving security and scalability over existing solutions with minimal performance impact.

Contribution

The paper presents a novel probabilistic management approach for resource-constrained in-DRAM trackers, enhancing Rowhammer mitigation resilience and scalability.

Findings

PROTEAS secures small trackers with 16 counters against low-threshold Rowhammer attacks.

PROTEAS achieves 11X-19X greater resilience compared to Samsung's DSAC.

Less than 3% slowdown incurred by PROTEAS.

Abstract

This paper focuses on mitigating DRAM Rowhammer attacks. In recent years, solutions like TRR have been deployed in DDR4 DRAM to track aggressor rows and then issue a mitigative action by refreshing neighboring victim rows. Unfortunately, such in-DRAM solutions are resource-constrained (only able to provision few tens of counters to track aggressor rows) and are prone to thrashing based attacks, that have been used to fool them. Secure alternatives for in-DRAM trackers require tens of thousands of counters. In this work, we demonstrate secure and scalable rowhammer mitigation using resource-constrained trackers. Our key idea is to manage such trackers with probabilistic management policies (PROTEAS). PROTEAS includes component policies like request-stream sampling and random evictions which enable thrash-resistance for resource-constrained trackers. We show that PROTEAS can secure small in-DRAM trackers (with 16 counters per DRAM bank) even when Rowhammer thresholds drop to 500 while incurring less than 3% slowdown. Moreover, we show that PROTEAS significantly outperforms a recent similar probabilistic proposal from Samsung (called DSAC) while achieving 11X - 19X the resilience against Rowhammer.