Innovative audio mosaic technique by permutations

Smart assistants have been indispensable mechanisms on electronic devices nowadays. However, as smart devices become prevalent everywhere, eavesdropping attacks could be encountered. Hence, information security is very important. Lately, we proposed a new efficient cryptographic mosaic technique, namely efficient recoverable cryptographic mosaic technique by permutations, for image mosaicing. In this paper, we further extend this mosaic technique for audio signals. To evaluate the effectiveness of this new audio-mosaicing scheme, here we propose a new audio signal-discrepancy measure, namely KullbackLeibler divergence of spectrogram (spec-KLD). We also relate this spec-KLD measure to the well-known signal-to-noise ratio (SNR) by benchmarking the signal destructuring effect. We also present the audio-mosaicing results based on speech recognition by Siri to demonstrate that our proposed approach can greatly (successfully) destroy the speech intelligibility for information hiding. The intelligence loss of speech is also enumerated in terms of spec-KLD and SNR.