Journal
PROCEEDINGS OF THE 2019 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY (CCS'19)
Volume -, Issue -, Pages 1149-1162Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3319535.3339810
Keywords
Device Fingerprinting; Electromagnetic Radiation; CPU; Smart Devices
Categories
Funding
- China NSFC [61702451]
- ZJNSF Grant [LGG19F020020]
- Fundamental Research Funds for the Central Universities [2019QNA4027]
Ask authors/readers for more resources
With the widespread use of smart devices, device authentication has received much attention. One popular method for device authentication is to utilize internally-measured device fingerprints, such as device ID, software or hardware-based characteristics. In this paper, we propose DeMiCPU, a stimulation-response-based device fingerprinting technique that relies on externally-measured information, i.e., magnetic induction (MI) signals emitted from the CPU module that consists of the CPU chip and its affiliated power supply circuits. The key insight of DeMiCPU is that hardware discrepancies essentially exist among CPU modules and thus the corresponding MI signals make promising device fingerprints, which are difficult to be modified or mimicked. We design a stimulation and a discrepancy extraction scheme and evaluate them with 90 mobile devices, including 70 laptops (among which 30 are of totally identical CPU and operating system) and 20 smartphones. The results show that DeMiCPU can achieve 99.1% precision and recall on average, and 98.6% precision and recall for the 30 identical devices, with a fingerprinting time of 0.6 s. In addition, the performance can be further improved to 99.9% with multi-round fingerprinting.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available