  A Physical unclonable functions (PUF), alike a fingerprint, exploits
manufacturing randomness to endow each physical item with a unique identifier.
One primary PUF application is the secure derivation of volatile cryptographic
keys using a fuzzy extractor comprising of two procedures: i) secure sketch;
and ii) entropy extraction. Although the entropy extractor can be lightweight,
the overhead of the secure sketch responsible correcting naturally noisy PUF
responses is usually costly. We observe that, in general, response
unreliability with respect to a enrolled reference measurement increases with
increasing differences between the in-the-field PUF operating condition and the
operating condition used in evaluating the enrolled reference response. For the
first time, we exploit such an important but inadvertent observation. In
contrast to the conventional single reference response enrollment, we propose
enrolling multiple reference responses (MRR) subject to the same challenge but
under multiple distinct operating conditions. The critical observation here is
that one of the reference operating conditions is likely to be closer to the
operating condition of the field deployed PUF, thus, resulting in minimizing
the expected unreliability when compared to the single reference under the
nominal condition. Overall, MRR greatly reduces the demand for the expected
number of erroneous bits for correction and, subsequently, achieve a
significant reduction in the error correction overhead. The significant
implementation efficiency gains from the proposed MRR method is demonstrated
from software implementations of fuzzy extractors on batteryless resource
constraint computational radio frequency identification devices, where
realistic PUF data is collected from the embedded intrinsic SRAM PUFs.
