SoK: Systematizing a Decade of Architectural RowHammer Defenses Through the Lens of Streaming Algorithms
Michael Jaemin Kim, Seungmin Baek, Jumin Kim, Hwayong Nam, Nam Sung Kim, Jung Ho Ahn

TL;DR
This paper systematically reviews a decade of architectural RowHammer defenses using streaming algorithms, providing a taxonomy, practical guides, and proposing new algorithms to enhance security and efficiency.
Contribution
It introduces a comprehensive taxonomy of 48 defenses, maps them to streaming algorithms, and offers practical guides and new algorithms like StickySampling for improved security.
Findings
Mapped multiple defenses to streaming algorithms
Provided practical guides for defense selection
Proposed new algorithms like StickySampling
Abstract
A decade after its academic introduction, RowHammer (RH) remains a moving target that continues to challenge both the industry and academia. With its potential to serve as a critical attack vector, the ever-decreasing RH threshold now threatens DRAM process technology scaling, with a superlinearly increasing cost of RH protection solutions. Due to their generality and relatively lower performance costs, architectural RH solutions are the first line of defense against RH. However, the field is fragmented with varying views of the problem, terminologies, and even threat models. In this paper, we systematize architectural RH defenses from the last decade through the lens of streaming algorithms. We provide a taxonomy that encompasses 48 different works. We map multiple architectural RH defenses to the classical streaming algorithms, which extends to multiple proposals that did not…
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Taxonomy
TopicsSecurity and Verification in Computing · Physical Unclonable Functions (PUFs) and Hardware Security · Advanced Malware Detection Techniques
