Controllable Key Agreement With Correlated Noise

The problem of secret-key-based authentication under privacy and storage constraints on the source sequence is considered. Identifier measurement channels during authentication are assumed to be controllable via a cost-constrained action sequence. Inner and outer bounds for the key-leakage-storage-cost regions are derived for a generalization of the classic two-terminal key agreement model. Additions to the model are that the encoder observes a noisy version of a remote source, and this 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 key generated by an encoder is extended to the randomized models, where a 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. Achievable (key, storage, cost) tuples are evaluated for binary identifiers and measurement channels represented as a mixture of binary symmetric subchannels. Significant gains from using an action sequence are illustrated to motivate the use of low-complexity transform-coding algorithms with cost-constrained actions.

[1]  Tobias J. Oechtering,et al.  Source Coding Problems With Conditionally Less Noisy Side Information , 2012, IEEE Transactions on Information Theory.

[2]  H. Vincent Poor,et al.  Biometric and Physical Identifiers with Correlated Noise for Controllable Private Authentication , 2020, 2020 IEEE International Symposium on Information Theory (ISIT).

[3]  Matthieu R. Bloch,et al.  Physical Layer Security , 2020, Encyclopedia of Wireless Networks.

[4]  Onur Günlü,et al.  DCT based ring oscillator Physical Unclonable Functions , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[5]  R. Pappu,et al.  Physical One-Way Functions , 2002, Science.

[6]  H. Vincent Poor,et al.  Privacy–Security Trade-Offs in Biometric Security Systems—Part I: Single Use Case , 2011, IEEE Transactions on Information Forensics and Security.

[7]  Onur Günlü Key Agreement with Physical Unclonable Functions and Biometric Identifiers , 2019 .

[8]  Imre Csiszár,et al.  Common randomness and secret key generation with a helper , 2000, IEEE Trans. Inf. Theory.

[9]  Claudia Eckert,et al.  Improving the quality of ring oscillator PUFs on FPGAs , 2010, WESS '10.

[10]  Rudolf Ahlswede,et al.  Common randomness in information theory and cryptography - I: Secret sharing , 1993, IEEE Trans. Inf. Theory.

[11]  Himanshu Tyagi,et al.  Converses For Secret Key Agreement and Secure Computing , 2014, IEEE Transactions on Information Theory.

[12]  Remi A. Chou,et al.  Separation of Reliability and Secrecy in Rate-Limited Secret-Key Generation , 2012, IEEE Transactions on Information Theory.

[13]  Vinod M. Prabhakaran,et al.  Secrecy via Sources and Channels , 2008, IEEE Transactions on Information Theory.

[14]  A. D. Wyner,et al.  The wire-tap channel , 1975, The Bell System Technical Journal.

[15]  Tom Gaertner,et al.  Biometric Systems Technology Design And Performance Evaluation , 2016 .

[16]  Frans M. J. Willems,et al.  Biometric Systems: Privacy and Secrecy Aspects , 2009, IEEE Transactions on Information Forensics and Security.

[17]  Jack K. Wolf,et al.  Noiseless coding of correlated information sources , 1973, IEEE Trans. Inf. Theory.

[18]  Suhas N. Diggavi,et al.  Secret-Key Generation Using Correlated Sources and Channels , 2009, IEEE Transactions on Information Theory.

[19]  Haim H. Permuter,et al.  Source Coding With a Side Information “Vending Machine” , 2009, IEEE Transactions on Information Theory.

[20]  Remi A. Chou,et al.  Polar coding for secret-key generation , 2013, 2013 IEEE Information Theory Workshop (ITW).

[21]  Onur Günlü,et al.  Code Constructions for Physical Unclonable Functions and Biometric Secrecy Systems , 2017, IEEE Transactions on Information Forensics and Security.

[22]  Giuseppe Caire,et al.  Controllable Identifier Measurements for Private Authentication With Secret Keys , 2018, IEEE Transactions on Information Forensics and Security.

[23]  Aylin Yener,et al.  A New Wiretap Channel Model and Its Strong Secrecy Capacity , 2017, IEEE Transactions on Information Theory.

[24]  Onur Günlü,et al.  Private Authentication with Physical Identifiers Through Broadcast Channel Measurements , 2019, 2019 IEEE Information Theory Workshop (ITW).

[25]  Blaise L. P. Gassend,et al.  Physical random functions , 2003 .

[26]  Chandra Nair,et al.  The capacity region of a class of broadcast channels with a sequence of less noisy receivers , 2010, 2010 IEEE International Symposium on Information Theory.

[27]  U. Maurer,et al.  Secret key agreement by public discussion from common information , 1993, IEEE Trans. Inf. Theory.

[28]  Amin Gohari,et al.  Achievability Proof via Output Statistics of Random Binning , 2012, IEEE Transactions on Information Theory.

[29]  Onur Günlü,et al.  Secure and Reliable Key Agreement with Physical Unclonable Functions † , 2018, IACR Cryptol. ePrint Arch..

[30]  Onur Günlü,et al.  Privacy, Secrecy, and Storage With Multiple Noisy Measurements of Identifiers , 2016, IEEE Transactions on Information Forensics and Security.