Computer-implemented method and apparatus for audio data hiding

• US 7,058,570 B1
• Filed: 02/10/2000
• Issued: 06/06/2006
• Est. Priority Date: 02/10/2000
• Status: Expired due to Fees

• Current Assignee: Matsushita Electric Industrial Company Limited (Panasonic Holdings Corporation)
• Original Assignee: Matsushita Electric Industrial Company Limited (Panasonic Holdings Corporation)
• Inventors: Yu, Hong Heather, Li, Xin
• Primary Examiner(s): Young, Wayne
• Assistant Examiner(s): Jackson, Jakieda R.
• Application Number:
  US09/499,525
• Time in Patent Office: 2,308 Days
• Field of Search: 704/270, 704/221, 704/222, 704/219, 704/258, 382/100, 713/176
• US Class Current: 704/219
• CPC Class Codes: G10L 19/018 Audio watermarking, i.e. embedding inaudible data in the audio signal
• CPC Class Codes: G10L 25/24 the extracted parameters being the cepstrum

Abstract

A computer-implemented method and apparatus for embedding hidden data in an audio signal. An audio signal is received in a base domain and then transformed into a non-base domain, such as cepstrum domain or LP residue domain. The statistical mean manipulation is employed on selected transform coefficients to embed hidden data. The introduced distortion is controlled by psychoacoustic model to ensure the imperceptibility of the embedded hidden data. Scrambling techniques can be plugged in to further increase the security of the data hiding system. The present new audio data hiding scheme provides transparent audio quality, sufficient embedding capacity, and high survivability over a wide range of common signal processing attacks.

Claims

1. A computer-implemented method for embedding hidden data in an audio signal, comprising the steps of:

receiving the audio signal in a base domain;

transforming the received audio signal to one of a linear prediction residue domain and a cepstrum domain, wherein transformation of the received audio signal to the cepstrum domain includes a fast Fourier transform, followed by a logarithmic operation, and then an inverse fast Fourier transform; and

embedding the hidden data in one of the linear prediction residue domain and the cepstrum domain via parametric representation of the audio signal by manipulating statistical mean of selected transform coefficients, and applying a scrambling technique to the transform coefficients with a scrambling filter kept as a secret key by a content owner.

2. The method of claim 1 further comprising the step of:

transforming the received audio signal to one of the linear prediction residue domain and the cepstrum domain such that transform domain coefficients are generated that are indicative of the transformed audio signal.

3. The method of claim 1 further comprising the steps of:

transforming the received audio signal to one of the linear prediction residue domain and the cepstrum domain such that transform domain coefficients are generated that are indicative of the transformed audio signal; and

manipulating a statistical measure of a selected subset of the transform domain coefficients in order to embed the hidden data.

4. The method of claim 3 further comprising the step of:

modulating the embedded data with at least one predetermined statistical feature of the transformed audio signal.

5. The method of claim 3 further comprising the step of:

increasing the amplitude of at least one predetermined feature of the transformed audio signal so that statistical mean of the predetermined feature is positive for embedding a bit of one in the audio signal.

6. The method of claim 1 further comprising the step of:

using a psycho-acoustic model to control inaudibility of the embedded data.

7. The method of claim 1 further comprising the steps of:

generating an inverse transformation signal using the embedded hidden data that is in the transformed audio signal;

receiving an attack upon the generated inverse transformation signal;

transforming the attacked inverse transformation signal to a non-base domain so as to generate a second transformed audio signal that is in the non-base domain; and

extracting the embedded hidden data from the second transformed audio signal.

8. The method of claim 1 further comprising the steps of:

transforming the received audio signal to the cepstrum domain;

embedding the hidden data in the cepstrum domain; and

enforcing a positive mean to embed a “

1” and

keeping a zero mean intact to embed a “

0”

in the cepstrum domain.

9. The method of claim 1, wherein embedding occurs as a direct result of manipulating the statistical mean of the selected features of the audio signal with respect to a predefined mean threshold.

10. The method of claim 9, wherein embedding occurs by manipulating statistical mean of selected features, including embedding one kind of two kinds of bits by enforcing a positive mean for features selected to carry the first kind of bit, and embedding another kind of the two kinds of bits by enforcing a mean not greater than zero for features selected to carry the other kind of bit.

11. The method of claim 9, further comprising employing a procedure to remove a biased mean of selected features prior to embedding.

12. The method of claim 9, further comprising:

embedding the hidden data in the cepstrum domain; and

keeping a zero mean intact to embed the other kind of bit in the cepstrum domain.

13. A computer-implemented apparatus for embedding hidden data in an audio signal, comprising the steps of:

a data input device for receiving the audio signal in a base domain;

a signal transformer connected to the data input device for transforming the received audio signal to one of a linear prediction domain and a cepstrum domain, wherein transformation of the received audio signal to the cepstrum domain includes a fast Fourier transform, followed by a logarithmic operation, and then an inverse fast Fourier transform; and

an embedder connected to the signal transformer for embedding the hidden data in one of the linear prediction domain and the cepstrum domain of the audio signal by manipulating statistical mean of selected transform coefficients, and applying a scrambling technique to the transform coefficients with a scrambling filter kept as a secret key by a content owner.

14. The apparatus of claim 13 wherein the signal transformer transforms the received audio signal to the non-base domain such that transform domain coefficients are generated that are indicative of the transformed non-base domain audio signal, said embedder manipulating a statistical measure of a selected subset of the transform domain coefficients in order to embed the hidden data.

15. The apparatus of claim 13 further comprising:

a psycho-acoustic model to control inaudibility of the embedded data.

16. The apparatus of claim 13 wherein the transformer transforms the received audio signal to the cepstrum domain, said embedder embedding the hidden data in the cepstrum domain by enforcing a positive mean to embed a “

1” and

keeping a zero mean intact to embed a “

0”

in the cepstrum domain.

17. A computer-implemented method for embedding hidden data in an audio signal, comprising the steps of:

receiving the audio signal in a base domain;

transforming the received audio signal to a linear prediction residue domain; and

embedding the hidden data in the linear prediction residue domain via parametric representation of the audio signal by manipulating statistical mean of selected transform coefficients, and applying a scrambling technique to the transform coefficients with a scrambling filter kept as a secret key by a content owner.

18. The method of claim 17 further comprising the step of:

transforming the received audio signal to the linear prediction residue domain such that transform domain coefficients are generated that are indicative of the transformed audio signal.

19. The method of claim 18 further comprising the steps of:

manipulating a statistical measure of a selected subset of the transform domain coefficients in order to embed the hidden data.

20. The method of claim 19 further comprising the step of:

modulating the embedded data with at least one predetermined statistical feature of the transformed audio signal.

21. The method of claim 20 further comprising the step of:

increasing the amplitude of at least one predetermined feature of the transformed audio signal so that statistical mean of the predetermined feature is positive for embedding a bit of one in the audio signal.

22. The method of claim 17 further comprising the step of:

using a psycho-acoustic model to control inaudibility of the embedded data.

23. The method of claim 17 further comprising the steps of:

generating an inverse transformation signal using the embedded hidden data that is in the transformed audio signal;

receiving an attack upon the generated inverse transformation signal;

transforming the attacked inverse transformation signal to a non-base domain so as to generate a second transformed audio signal that is in the non-base domain; and

extracting the embedded hidden data from the second transformed audio signal.