Exploiting Switching of Transistors in Digital Electronics for RFID Tag Design

Cheng, Chia-Lin; Nguyen, Luong N.; Prvulovic, Milos; Zajić, Alenka

doi:10.1109/jrfid.2019.2894508

Cited by 11 publications

(1 citation statement)

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“…Measurements of unintended EM emanations are, by their nature of being unintended, extremely weak and susceptible to noise. By applying a strong source frequency to the surface of a DuT and receiving the reflections, a method known as backscattering, the signal to noise ratio (SNR) of the EM side-channel can be improved [10], [24]- [26]. An additional benefit of backscattering for circuit fingerprinting is that the reflected power contains not only modulated circuit activity, but also reflections of characteristic impedances from dormant portions of the DuT.…”

Section: Introductionmentioning

confidence: 99%

Circuit Activity Fingerprinting Using Electromagnetic Side-Channel Sensing and Digital Circuit Simulations

et al. 2022

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This paper introduces a novel circuit identification method based on "fingerprints" of periodic circuit activity that does not rely on any circuit-specific reference measurements. We capture these "fingerprints", consisting of fifty harmonics of the circuit activity, using digital circuit simulations and nearfield measurements of the EM backscattering side-channel. Utilizing a novel technique and algorithm, we augment our measurements, removing sources of noise and other irregularities not present in the simulation, in order to relate an unknown circuit measurement with a known circuit simulation. A matching threshold of less than 1 dB difference between the simulated and measured fingerprints is set, and the matching performance is evaluated across multiple hardware instances exhibiting a strong resistance to false positives. Using various match statistics, decisions on the circuit identity can be made based on the simulated and measured fingerprint pair with the best matching performance. The results show that we can identify fingerprints of digital circuits with up to 95% accuracy using the proposed method.

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Section: Introductionmentioning

confidence: 99%