Multi-Entity and Multi-Enrollment Key Agreement With Correlated Noise

A basic model for key agreement with a remote (or hidden) source is extended to a multi-user model with joint secrecy and privacy constraints over all entities that do not trust each other. Multiple entities using different measurements of the same source through broadcast channels (BCs) to agree on mutually-independent local secret keys are considered. Our model is the proper multi-user extension of the basic model since the encoder and decoder pairs are not assumed to trust other pairs, unlike assumed in the literature. Strong secrecy constraints imposed on all secret keys jointly, which is more stringent than separate secrecy leakage constraints for each secret key considered in the literature, are satisfied. Inner bounds for maximum key rate, and minimum privacy-leakage and databasestorage rates are proposed for any finite number of entities. Inner and outer bounds for degraded and less-noisy BCs are given to illustrate cases with strong privacy. A multi-enrollment model that is used for common physical unclonable functions is considered to establish inner and outer bounds for key-leakagestorage regions that differ only in the Markov chains imposed. For this special case, the encoder and decoder measurement channels have the same channel transition matrix and secrecy leakage is measured for each secret key separately. We illustrate cases for which it is useful to have multiple enrollments as compared to a single enrollment and vice versa.

[1]  Lieneke Kusters,et al.  Secret-Key Capacity Regions for Multiple Enrollments With an SRAM-PUF , 2019, IEEE Transactions on Information Forensics and Security.

[2]  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.

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

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

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

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

[7]  Haim H. Permuter,et al.  Fourier-Motzkin Elimination Software for Information Theoretic Inequalities , 2016, ArXiv.

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

[9]  Ingrid Verbauwhede,et al.  A soft decision helper data algorithm for SRAM PUFs , 2009, 2009 IEEE International Symposium on Information Theory.

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

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

[12]  Haim H. Permuter,et al.  Coordination Capacity , 2009, IEEE Transactions on Information Theory.

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

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

[15]  Martin Wattenberg,et al.  A fuzzy commitment scheme , 1999, CCS '99.

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

[17]  Johannes B. Huber,et al.  Bounds on information combining , 2005, IEEE Transactions on Information Theory.

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

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

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

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

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

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

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

[25]  Chandra Nair,et al.  Capacity regions of two new classes of 2-receiver broadcast channels , 2009, 2009 IEEE International Symposium on Information Theory.

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

[27]  Alexander Schrijver,et al.  Theory of linear and integer programming , 1986, Wiley-Interscience series in discrete mathematics and optimization.

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

[29]  Stephen A. Benton,et al.  Physical one-way functions , 2001 .

[30]  Onur Günlü,et al.  Zero secrecy leakage for multiple enrollments of physical unclonable functions , 2018 .

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

[32]  Lieneke Kusters,et al.  Security of helper data schemes for SRAM-PUF in multiple enrollment scenarios , 2017, 2017 IEEE International Symposium on Information Theory (ISIT).

[33]  Patrizio Campisi,et al.  Security and Privacy in Biometrics , 2013, Springer London.

[34]  Rafail Ostrovsky,et al.  Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data , 2004, SIAM J. Comput..

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

[36]  Thomas M. Cover,et al.  Elements of information theory (2. ed.) , 2006 .

[37]  Matthieu R. Bloch,et al.  Strong Coordination of Signals and Actions Over Noisy Channels With Two-Sided State Information , 2020, IEEE Transactions on Information Theory.