Abstract
As electronic communications become more
prevalent, mobile and universal, the threats of data compromises
also accordingly loom larger. In the context of
a body sensor network (BSN), which permits pervasive
monitoring of potentially sensitive medical data, security
and privacy concerns are particularly important. It is a
challenge to implement traditional security infrastructures
in these types of lightweight networks since they are
by design limited in both computational and communication
resources. A key enabling technology for secure
communications in BSN's has emerged to be biometrics.
In this work, we present two complementary approaches
which exploit physiological signals to address security
issues: (1) a resource-efficient key management system
for generating and distributing cryptographic keys to
constituent sensors in a BSN; (2) a novel data scrambling
method, based on interpolation and random sampling, that
is envisioned as a potential alternative to conventional
symmetric encryption algorithms for certain types of data.
The former targets the resource constraints in BSN's, while
the latter addresses the fuzzy variability of biometric signals,
which has largely precluded the direct application of
conventional encryption. Using electrocardiogram (ECG)
signals as biometrics, the resulting computer simulations
demonstrate the feasibility and efficacy of these methods
for delivering secure communications in BSN's.