  Biometric key generation techniques are used to reliably generate
cryptographic material from biometric signals. Existing constructions require
users to perform a particular activity (e.g., type or say a password, or
provide a handwritten signature), and are therefore not suitable for generating
keys continuously. In this paper we present a new technique for biometric key
generation from free-text keystroke dynamics. This is the first technique
suitable for continuous key generation. Our approach is based on a scaled
parity code for key generation (and subsequent key reconstruction), and can be
augmented with the use of population data to improve security and reduce key
reconstruction error. In particular, we rely on linear discriminant analysis
(LDA) to obtain a better representation of discriminable biometric signals.
  To update the LDA matrix without disclosing user's biometric information, we
design a provably secure privacy-preserving protocol (PP-LDA) based on
homomorphic encryption. Our biometric key generation with PP-LDA was evaluated
on a dataset of 486 users. We report equal error rate around 5% when using LDA,
and below 7% without LDA.
