Polar codes for covert communications over asynchronous Discrete Memoryless Channels

We develop a covert communication scheme for binary-input asynchronous Discrete Memoryless Channels based on binary polar codes, in which legitimate parties exploit uncertainty created by both the channel noise and the time of transmission. The proposed code jointly ensures reliable communication for a legitimate receiver and low probability of detection with respect to an adversary, both observing noisy versions of the codewords. Binary polar codes are used to shape the weight distribution of codewords and ensure that the average weight decays as the block length grows. The performance of the proposed code is limited by the speed of polarization, which in turns controls the decay of the average codeword weight with the block length. Although the proposed construction falls short of achieving the performance of random codes, it inherits the low-complexity properties of polar codes.

[1]  Rüdiger L. Urbanke,et al.  Unified scaling of polar codes: Error exponent, scaling exponent, moderate deviations, and error floors , 2015, 2015 IEEE International Symposium on Information Theory (ISIT).

[2]  Rüdiger L. Urbanke,et al.  Achieving Marton’s Region for Broadcast Channels Using Polar Codes , 2014, IEEE Transactions on Information Theory.

[3]  Mayank Bakshi,et al.  Computationally efficient deniable communication , 2016, 2016 IEEE International Symposium on Information Theory (ISIT).

[4]  Remi A. Chou,et al.  Polar Coding for the Broadcast Channel With Confidential Messages: A Random Binning Analogy , 2016, IEEE Transactions on Information Theory.

[5]  Matthieu R. Bloch,et al.  Keyless asynchronous covert communication , 2016, 2016 IEEE Information Theory Workshop (ITW).

[6]  Andrew Thangaraj,et al.  Error-Control Coding for Physical-Layer Secrecy , 2015, Proceedings of the IEEE.

[7]  Mayank Bakshi,et al.  Reliable deniable communication: Hiding messages in noise , 2013, 2013 IEEE International Symposium on Information Theory.

[8]  Sergio Verdú,et al.  Approximation theory of output statistics , 1993, IEEE Trans. Inf. Theory.

[9]  Imre Csiszár,et al.  Information Theory - Coding Theorems for Discrete Memoryless Systems, Second Edition , 2011 .

[10]  Matthieu R. Bloch,et al.  Covert Communication Over Noisy Channels: A Resolvability Perspective , 2015, IEEE Transactions on Information Theory.

[11]  Erdal Arikan,et al.  Source polarization , 2010, 2010 IEEE International Symposium on Information Theory.

[12]  Erdal Arikan,et al.  Channel Polarization: A Method for Constructing Capacity-Achieving Codes for Symmetric Binary-Input Memoryless Channels , 2008, IEEE Transactions on Information Theory.

[13]  Lizhong Zheng,et al.  Fundamental Limits of Communication With Low Probability of Detection , 2015, IEEE Transactions on Information Theory.

[14]  Donald F. Towsley,et al.  LPD communication when the warden does not know when , 2014, 2014 IEEE International Symposium on Information Theory.

[15]  Matthieu R. Bloch,et al.  Optimal covert communications using pulse-position modulation , 2017, 2017 IEEE International Symposium on Information Theory (ISIT).

[16]  Joseph M. Renes,et al.  Noisy Channel Coding via Privacy Amplification and Information Reconciliation , 2010, IEEE Transactions on Information Theory.

[17]  Boulat A. Bash,et al.  Limits of Reliable Communication with Low Probability of Detection on AWGN Channels , 2012, IEEE Journal on Selected Areas in Communications.

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

[19]  Rüdiger L. Urbanke,et al.  Finite-Length Scaling for Polar Codes , 2013, IEEE Transactions on Information Theory.

[20]  Rüdiger L. Urbanke,et al.  Near-optimal finite-length scaling for polar codes over large alphabets , 2016, 2016 IEEE International Symposium on Information Theory (ISIT).

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