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

Fuente: arXiv
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Auteurs principaux: Jaleel, Aamer, Keckler, Stephen W., Saileshwar, Gururaj
Format: Preprint
Publié: 2024
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author Jaleel, Aamer
Keckler, Stephen W.
Saileshwar, Gururaj
author_facet Jaleel, Aamer
Keckler, Stephen W.
Saileshwar, Gururaj
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2404_16256
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Probabilistic Tracker Management Policies for Low-Cost and Scalable Rowhammer Mitigation
Jaleel, Aamer
Keckler, Stephen W.
Saileshwar, Gururaj
Cryptography and Security
Hardware Architecture
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.
title Probabilistic Tracker Management Policies for Low-Cost and Scalable Rowhammer Mitigation
topic Cryptography and Security
Hardware Architecture
url https://arxiv.org/abs/2404.16256