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START: Scalable Tracking for any Rowhammer Threshold

Anish Saxena, Moinuddin K. Qureshi

202420 citationsDOI

Abstract

The Rowhammer vulnerability is worsening, with the Rowhammer Threshold (T <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RH</inf> ) reducing from 139K to 4.8K activations over the last decade. As thresholds reduce further, the number of possible aggressor rows increases inversely, making it difficult to reliably track such rows in a storage-efficient manner for typical Rowhammer defenses. To be secure at lower thresholds, academic trackers like Graphene must dedicate prohibitively high storage (hundreds of KBs to MBs) at the chip's design time. Recent in-DRAM trackers from the industry, such as DSAC-TRR, perform approximate tracking and sacrifice guaranteed protection for reduced storage overheads, leaving DRAM vulnerable to Rowhammer attacks. Ideally, we seek a configurable tracker that is secure and precise, incurs negligible dedicated storage and performance overheads, and scales at deployment to track arbitrarily low thresholds. To that end, we propose START - a Scalable Tracker for Any Rowhammer Threshold. Rather than relying on dedicated SRAM structures, START dynamically repurposes a small fraction of the Last-Level Cache (LLC) to store tracking metadata. START leverages the observation that while the memory contains millions of rows, typical workloads touch only a small subset of rows within a refresh period of 64ms. Thus, allocating tracking entries on demand reduces storage significantly. If the application does not access many rows in memory, START does not reserve any LLC capacity. Otherwise, START dynamically uses 1-way, 2-way, or 8-way of the cache set based on demand. START consumes, on average, 9.4% of the LLC capacity to store metadata, which is 5 × lower compared to dedicating a counter in LLC for each row in memory. We also propose START-M, a memory-mapped START for large-memory systems. Our designs require only 4KB SRAM for newly added structures and perform within 1% of idealized tracking even at T <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RH</inf> of less than 100.

Topics & Concepts

RowDramScalabilityComputer scienceStatic random-access memoryCacheBitTorrent trackerEmbedded systemOperating systemComputer hardwareDatabaseComputer visionEye trackingSecurity and Verification in ComputingAdvanced Memory and Neural ComputingDiamond and Carbon-based Materials Research
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