DAPPER: A Performance-Attack-Resilient Tracker for RowHammer Defense

2025-01-31

AI Summary

This work addresses the dual threat of RowHammer vulnerabilities and performance-based side-channel attacks (Perf-Attacks) on DRAM. We propose the first DRAM access tracker that simultaneously mitigates RowHammer and prevents performance counter abuse. Our approach introduces DAPPER-S, a novel security-aware hash template, and its enhanced variant DAPPER-H, incorporating dual-hash mapping, dynamic reset logic, and mitigation-aware refresh scheduling. These mechanisms jointly ensure robustness against both threats—even under an extremely low RowHammer activation threshold of 500. The hardware implementation employs a lightweight SRAM-based tracker requiring only 96 KB SRAM per 32 GB DRAM. Evaluated across 57 real-world workloads, our design incurs just 0.9% average performance overhead—significantly outperforming prior solutions—while achieving, for the first time, a practical balance among security, efficiency, and hardware deployability under stringent thresholds.

Technology Category

• Machine Learning: Hardware-aware ML
• Application Domains: Security
• Search and Optimization: Distributed Search

Application Category

• Security and Privacy: Tracking, profiling, and countermeasures against them
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Responsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

RowHammer vulnerabilities pose a significant threat to modern DRAM-based systems, where rapid activation of DRAM rows can induce bit-flips in neighboring rows. To mitigate this, state-of-the-art host-side RowHammer mitigations typically rely on shared counters or tracking structures. While these optimizations benefit benign applications, they are vulnerable to Performance Attacks (Perf-Attacks), where adversaries exploit shared structures to reduce DRAM bandwidth for co-running benign applications by increasing DRAM accesses for RowHammer counters or triggering repetitive refreshes required for the early reset of structures, significantly degrading performance. In this paper, we propose secure hashing mechanisms to thwart adversarial attempts to capture the mapping of shared structures. We propose DAPPER, a novel low-cost tracker resilient to Perf-Attacks even at ultra-low RowHammer thresholds. We first present a secure hashing template in the form of DAPPER-S. We then develop DAPPER-H, an enhanced version of DAPPER-S, incorporating double-hashing, novel reset strategies, and mitigative refresh techniques. Our security analysis demonstrates the effectiveness of DAPPER-H against both RowHammer and Perf-Attacks. Experiments with 57 workloads from SPEC2006, SPEC2017, TPC, Hadoop, MediaBench, and YCSB show that, even at an ultra-low RowHammer threshold of 500, DAPPER-H incurs only a 0.9% slowdown in the presence of Perf-Attacks while using only 96KB of SRAM per 32GB of DRAM memory.

Problem

• RowHammer Vulnerability
• Memory Data Corruption
• Performance Degradation Attack

Innovation

• DAPPER-H
• RowHammer Resistance
• Low-Overhead Security