Paper 2020/257

Biometric and Physical Identifiers with Correlated Noise for Controllable Private Authentication

Onur Gunlu, Rafael F. Schaefer, and H. Vincent Poor


The problem of secret-key based authentication under privacy and storage constraints on the source sequence is considered. The identifier measurement channels during authentication are assumed to be controllable via a cost-constrained action sequence. Single-letter inner and outer bounds for the key-leakage-storage-cost regions are derived for a generalization of a classic two-terminal key agreement model with an eavesdropper that observes a sequence that is correlated with the sequences observed by the legitimate terminals. The additions to the model are that the encoder observes a noisy version of a remote source, and the noisy output and the remote source output together with an action sequence are given as inputs to the measurement channel at the decoder. Thus, correlation is introduced between the noise components on the encoder and decoder measurements. The model with a secret-key generated by an encoder is extended to the randomized models, where a secret-key is embedded to the encoder. The results are relevant for several user and device authentication scenarios including physical and biometric identifiers with multiple measurements that provide diversity and multiplexing gains. To illustrate the behavior of the rate region, achievable (secret-key rate, storage-rate, cost) tuples are given for binary identifiers and measurement channels that can be represented as a set of binary symmetric subchannels. The gains from using an action sequence such as a large secret-key rate at a significantly small hardware cost, are illustrated to motivate the use of low-complexity transform-coding algorithms with cost-constrained actions.

Available format(s)
Publication info
Preprint. MINOR revision.
information theorybroadcast channelkey agreementone-way functions
Contact author(s)
guenlue @ tu-berlin de
2020-02-25: received
Short URL
Creative Commons Attribution


      author = {Onur Gunlu and Rafael F.  Schaefer and H.  Vincent Poor},
      title = {Biometric and Physical Identifiers with Correlated Noise for Controllable Private Authentication},
      howpublished = {Cryptology ePrint Archive, Paper 2020/257},
      year = {2020},
      note = {\url{}},
      url = {}
Note: In order to protect the privacy of readers, does not use cookies or embedded third party content.