An audio encryption technique through compressive sensing and Arnold transform

In this paper, an audio encryption scheme using compressive sensing (CS) and Arnold transform-based scrambling is presented. In the proposed method, compressive sensing is done by using a key-based measurement matrix and the scrambling is carried out with the help of a key-based Arnold matrix. The use of these key-based matrices not only provides better security but also do away with their transmission and storage requirement. The measurement matrix is constructed by using the random numbers generated by a linear feedback shift register (LFSR) whose initial state is generated by a piece wise linear chaotic map (PWLCM), using three 32-bit keys whereas the Arnold matrix is constructed by the random numbers generated by using another 32-bit secret key, PWLCM and a logistic map. By combining secure compressive sensing and Arnold scrambling techniques, very high security can be ensured in addition to efficient channel usage, good resistivity to noise, best reconstruction performance, little encoder complexity and excellent scrambling of data. Experimental results prove the effectiveness of the proposed scheme.

[1]  Alfonso Ortega,et al.  Audio scrambling technique based on cellular automata , 2012, Multimedia Tools and Applications.

[2]  Subhash C. Kak,et al.  Multilevel Indexed Quasigroup Encryption for Data and Speech , 2009, IEEE Transactions on Broadcasting.

[3]  Seiichi Uchida,et al.  A parallel image encryption method based on compressive sensing , 2012, Multimedia Tools and Applications.

[4]  David L Donoho,et al.  Compressed sensing , 2006, IEEE Transactions on Information Theory.

[5]  Liang Chen,et al.  Scrambling-based speech encryption via compressed sensing , 2012, EURASIP J. Adv. Signal Process..

[6]  P. P. Deepthi,et al.  Compressive Sensing Based Audio Scrambling Using Arnold Transform , 2014, SNDS.

[7]  Juan Carlos De Martin,et al.  Perception-based partial encryption of compressed speech , 2002, IEEE Trans. Speech Audio Process..

[8]  E.J. Candes,et al.  An Introduction To Compressive Sampling , 2008, IEEE Signal Processing Magazine.

[9]  Sudhish N. George,et al.  A Secure LFSR Based Random Measurement Matrix for Compressive Sensing , 2014 .

[10]  Yiqing Lin,et al.  A secure and robust audio watermarking scheme using multiple scrambling and adaptive synchronization , 2007, 2007 6th International Conference on Information, Communications & Signal Processing.

[11]  Hugo Krawczyk,et al.  LFSR-based Hashing and Authentication , 1994, CRYPTO.

[12]  Jian Zhang,et al.  A Block Location Scrambling Algorithm of Digital Image Based on Arnold Transformation , 2008, 2008 The 9th International Conference for Young Computer Scientists.

[13]  V. Senk,et al.  A new speech scrambling concept based on Hadamard matrices , 1997, IEEE Signal Processing Letters.

[14]  Joel A. Tropp,et al.  Greed is good: algorithmic results for sparse approximation , 2004, IEEE Transactions on Information Theory.

[15]  Romano Fantacci,et al.  A new speech signal scrambling method for secure communications: theory, implementation, and security evaluation , 1989, IEEE J. Sel. Areas Commun..

[16]  G. Sharma,et al.  On the security and robustness of encryption via compressed sensing , 2008, MILCOM 2008 - 2008 IEEE Military Communications Conference.

[17]  Shao Liping An n-Dimensional Space Audio Scrambling Algorithm Based on Random Matrix , 2010 .