2023/06/30 by Hari Venugopalan, Venugopalan, Hari, Kaustav Goswami +9 · 1 voice
Computer Science · #Advanced Steganography and Watermarking Techniques #Biometric Identification and Security #Internet Traffic Analysis and Secure E-voting #cs.CR
paper · pdf · doi:10.48550/arxiv.2307.00143
openalex publication_date 2023/06/30 · openalex created_date 2023/07/05 · openalex updated_date 2026/07/28
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.