Sparse representation based audio scrambling using cellular automata

This paper proposes a novel approach for scrambling the compressively sensed audio data. Two dimensional cellular automata (CA) based scrambling algorithm is proposed, in which the initial state matrix of CA is constructed by the random bit sequence generated by a linear feedback shift register (LFSR). Compressive sensing (CS) offers excellent robustness in the presence of noise and greater compression whereas CA offers excellent scrambling degree. This scrambling scheme ensures efficient channel usage, resistivity to noise, best signal to noise ratio and good scrambling of data. Experimental results confirm the effectiveness of the proposed scheme.