- This dataset consists of the memory access behavior of various applications including a mix of both normal applications and Rowhammer attacks, and associated code. The memory access data is generated using Gem5 v20.1.0.5. We use Gem5 to simulate a 4-core system with Linux OS in full-system mode. The data can be used for Rowhammer research or any other memory related research purpose.
- Total Size
- 6 files (2.23 GB)
- Data Citation
- Joardar, B. K., Bletsch, T.K., Chakrabarty, K. (2022). Data from: Machine learning-based rowhammer mitigation. Duke Research Data Repository. https://doi.org/10.7924/r4hh6p604
- DOI
- 10.7924/r4hh6p604
- Publication Date
- May 26, 2022
- ARK
- ark:/87924/r4hh6p604
- Affiliation
- Publisher
- Type
- Related Materials
- Contact
- Biresh Kumar Joardar, ORCiD: 0000-0002-7668-2824, bireshkumar.joardar@duke.edu
- Title
- Data from: Machine Learning-based Rowhammer Mitigation
- Repository
Thumbnail | Title | Date Uploaded | Visibility | Actions |
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adversarial.zip | 2022-05-26 | Download | |
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benign.zip | 2022-05-26 | ||
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blacksmith.zip | 2022-05-26 | Download | |
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code.zip | 2022-05-26 | Download | |
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n-sided.zip | 2022-05-26 | Download | |
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README.md | 2022-05-26 | Download |