Abstract
This paper analyses a novel countermeasure to Leakage Power Analysis Attacks based on the application of a random Body Bias voltage level at the beginning of the encryption process. The countermeasure effectiveness is established through the development of a theoretical model of the Pearson correlation coefficient in the presence of a varying body bias under both noiseless assumptions and in the presence of algorithmic noise, and through simulations on a partial cryptosystem implemented in 28 nm FDSOI technology. A study of the effect of averaging power measurements is also developed and contrasted against Monte Carlo simulations of the countermeasure scheme, effectively providing a floor for the increase in required measurements to identify the secret key.
Highlights
As technology nodes progress further into smaller nanometric scales, short-channel effects worsen, one of the most impactful short-channel effects being the increase of leakage currents
In this paper we explore the feasibility of utilizing a varying body bias as a countermeasure for Leakage-based Power Analysis Attacks (PAA) in systems implemented in Fully Depleted Silicon On Insulator (FDSOI) technology
The leakage current consumed by a register array implemented in FDSOI technology becomes a function of body bias
Summary
As technology nodes progress further into smaller nanometric scales, short-channel effects worsen, one of the most impactful short-channel effects being the increase of leakage currents. Moll: Analysis of Random Body Bias Application in FDSOI Cryptosystems as Countermeasure It is, understood that Power Attacks that rely on static power consumption typically convey poorer results than their dynamic power counterpart. This factor, coupled with comparatively smaller signals than those obtained through a dynamic power side-channel results in noisier data with smaller signal levels Despite this fact, several circumstances can enhance the effectiveness of leakage-based PAA. Extending the clock period allows the acquisition of an increasing number of samples of the signals of interest at closely spaced intervals of time This ‘‘oversampling’’ can be used to obtain averaged measurements, in what is called inter-trace averaging, to reduce overall non-algorithmic noise. In this paper we explore the feasibility of utilizing a varying body bias as a countermeasure for Leakage-based PAA in systems implemented in FDSOI technology.
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