TY - GEN
T1 - Innovative audio mosaic technique by permutations
AU - Sun, Elaine Y.N.
AU - Wu, Hsiao Chun
AU - Busch, Costas
AU - Huang, Scott C.H.
AU - Kuan, Yen Cheng
AU - Wu, Jonathan
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/27
Y1 - 2020/10/27
N2 - 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.
AB - 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.
KW - Information hiding
KW - Kullback-Leibler divergence (KLD)
KW - KullbackLeibler divergence of spectrogram (spec-KLD)
KW - Permutation
KW - Recoverable cryptographic mosaic
KW - Siri
KW - Spectrogram
UR - http://www.scopus.com/inward/record.url?scp=85103441881&partnerID=8YFLogxK
U2 - 10.1109/BMSB49480.2020.9379882
DO - 10.1109/BMSB49480.2020.9379882
M3 - Conference contribution
AN - SCOPUS:85103441881
T3 - IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB
BT - 15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020
PB - IEEE Computer Society
T2 - 15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020
Y2 - 27 October 2020 through 29 October 2020
ER -