FP-Rowhammer: DRAM-Based Device Fingerprinting
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866929552470573056 |
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| author | Venugopalan, Hari Goswami, Kaustav Din, Zainul Abi Lowe-Power, Jason King, Samuel T. Shafiq, Zubair |
| author_facet | Venugopalan, Hari Goswami, Kaustav Din, Zainul Abi Lowe-Power, Jason King, Samuel T. Shafiq, Zubair |
| contents | Device fingerprinting leverages attributes that capture heterogeneity in hardware and software configurations to extract unique and stable fingerprints. Fingerprinting countermeasures attempt to either present a uniform fingerprint across different devices through normalization or present different fingerprints for the same device each time through obfuscation. We present FP-Rowhammer, a Rowhammer-based device fingerprinting approach that can build unique and stable fingerprints even across devices with normalized or obfuscated hardware and software configurations. To this end, FP-Rowhammer leverages the DRAM manufacturing process variation that gives rise to unique distributions of Rowhammer-induced bit flips across different DRAM modules. Our evaluation on a test bed of 98 DRAM modules shows that FP-Rowhammer achieves 99.91% fingerprinting accuracy. FP-Rowhammer's fingerprints are also stable, with no degradation in fingerprinting accuracy over a period of ten days. We also demonstrate that FP-Rowhammer is efficient, taking less than five seconds to extract a fingerprint. FP-Rowhammer is the first Rowhammer fingerprinting approach that is able to extract unique and stable fingerprints efficiently and at scale. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2307_00143 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | FP-Rowhammer: DRAM-Based Device Fingerprinting Venugopalan, Hari Goswami, Kaustav Din, Zainul Abi Lowe-Power, Jason King, Samuel T. Shafiq, Zubair Cryptography and Security Device fingerprinting leverages attributes that capture heterogeneity in hardware and software configurations to extract unique and stable fingerprints. Fingerprinting countermeasures attempt to either present a uniform fingerprint across different devices through normalization or present different fingerprints for the same device each time through obfuscation. We present FP-Rowhammer, a Rowhammer-based device fingerprinting approach that can build unique and stable fingerprints even across devices with normalized or obfuscated hardware and software configurations. To this end, FP-Rowhammer leverages the DRAM manufacturing process variation that gives rise to unique distributions of Rowhammer-induced bit flips across different DRAM modules. Our evaluation on a test bed of 98 DRAM modules shows that FP-Rowhammer achieves 99.91% fingerprinting accuracy. FP-Rowhammer's fingerprints are also stable, with no degradation in fingerprinting accuracy over a period of ten days. We also demonstrate that FP-Rowhammer is efficient, taking less than five seconds to extract a fingerprint. FP-Rowhammer is the first Rowhammer fingerprinting approach that is able to extract unique and stable fingerprints efficiently and at scale. |
| title | FP-Rowhammer: DRAM-Based Device Fingerprinting |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2307.00143 |