Audio Watermarking and Steganography

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Some Audio Steganography and Watermarking algorithms

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Audio Watermarking and Steganography

  1. 1. AUDIO WATERMARKING AND STEGANOGRAPHY Anirudh Shekhawat Manan Shah Prateek Srivastava Pratik Poddar Guided by: Prof. Bernard Menezes
  2. 2. DIGITAL WATERMARKING  Embedding perceptually transparent data in digital media  Watermark can be detected and retrieved by a computer algorithm  Applications include broadcast monitoring, fingerprinting, copyright protection and steganography
  3. 3. STEGANOGRAPHY  Steganography literally means "secret writing”  Hiding data in a digital media  Avoids the suspicion and scrutiny an encrypted message would arouse  Applications include "covert communication”  Examples from history - Invisible ink, Scalp tattoo, Pinholes
  4. 4. APPLICATIONS
  5. 5. COPYRIGHT PROTECTION  Ownership information can be embedded in the media  Presence of the watermark can be demonstrated to prove ownership  The watermark must survive compression
  6. 6. FINGERPRINTING  Embedding a serial number in each copy of a media before distribution  Can be used to trace down the originator of a particular illegal copy of media  The watermark must be secure against attacks
  7. 7. BROADCAST MONITORING  Programs and advertisements broadcasted can be monitored by an automated system  Illegal broadcasts can be identified by monitoring satellite nodes  High Bit rate and low complexity are required
  8. 8. COVERT COMMUNICATION  Embedding data such that existence of a watermark cannot be detected  Aimed at protecting the sender and receiver rather than the message  Terrorists have been reported to hide messages in images to communicate
  9. 9. CHARACTERISTICS OF A WATERMARKING ALGORITHM
  10. 10. PERCEPTUAL TRANSPARENCY  Primary requirement in watermarking  Watermark should be imperceptible to human auditory system  Watermarking is more difficult for audio as compared to images
  11. 11. WATERMARK BIT RATE  Represented in bits per second (bps)  Required rates vary across applications (0.5 bps in copyright protection and 15 bps in broadcast monitoring)  Attainable values depend upon level of compression of audio
  12. 12. ROBUSTNESS  The ability of the watermark to survive common signal processing manipulations  Required against a predefined set of manipulations  Required in some applications (radio broadcast monitoring) but not at all required in some (tampering detection)
  13. 13. BLIND AND INFORMED DETECTION  Informed: with access to original(host) audio  Blind: without access to original audio  Informed techniques are more secure  Examples  Blind: Tampering detection, Information Carrier  Informed: Steganography
  14. 14. SECURITY  Adversary must not be able to detect the existence of embedded data  Not be able to extract or modify the data without the secret key  In some cases the watermark is encrypted before being embedded
  15. 15. ALGORITHMS AND DEMO
  16. 16. 1) LEAST SIGNIFICANT BIT ENCODING  Watermark added in the least significant bit of amplitude  Easy to embed and retrieve  High bit rate  Low robustness
  17. 17. WATERMARKING, COMPRESSION & REDUNDANCY  Lossy compression destroys watermark.  To make watermark robust against compression, we need sufficient redundancy  LSB encoding: Robustness vs Imperceptibility?  LSB Watermarking in JPEG done   Possible for MP3?
  18. 18. 2) PHASE MODULATION  Embed watermark by modulating phase in host audio  Robust against signal processing manipulations  Extraction or detection of watermark needs original audio  Suitable for applications where security and robustness are important, e.g. copyright protection
  19. 19. 3) FREQUENCY DOMAIN STEGANOGRAPHY  Shanon Sampling theorem  Sampling rate for CD is 44.1KHz the highest frequency is 18KHz  Average peak frequency which a human can hear is 18Khz 22 – 18 = 4KHz band goes unused
  20. 20. UNDERLYING PRINCIPLE  Use the 18Khz - 22KHz frequency band to hide the message Message signal Base signal Fig : Combined Signal
  21. 21. MERITS AND DEMERITS  Merits  Longer message can be hidden in a given base  Less likely to be affected by errors during transmission  Demerits  Message signal has limited frequency range  Low recovery quality
  22. 22. 4) ECHO HIDING  Embeds data by introducing “echo” in the original signal.  Resilient to lossy data compression algorithms.
  23. 23. ECHO ENCODING AND DECODING Encoding Decoding
  24. 24. THE END.. QUESTIONS?
  25. 25. REFERENCES  Juergen Seitz, Digital Watermarking for Digital Media, ISBN 159140519X, 2005, Information Resources Press, Arlington, VA, USA  Nedeljko Cvejic, Algorithms for audio watermarking and steganography, ISBN 9514273834, 2004, Oulu University Press, Oulu  C.H. Yeh & C.J Kuo, Digital watermarking through quasi m-arrays, Proceedings of the IEEE Workshop on Signal Processing Systems 1999, 456-461  Guy Belloch, Introduction to Data Compression, Draft version, Algorithms in the real world  Kuo S, Johnston J, Turin W & Quackenbush S Covert audio- watermarking using perceptually tuned signal independent multiband phase modulation, IEEE International Conference on Acoustics, Speech, and Signal Processing 2002, 1753-1756
  26. 26. REFERENCES  Foo, S.W., Yeo, T.H., & Huang, D.Y. (2001). An adaptive audio watermarking system. Proceedings of the IEEE Region 10 International Conference on Electrical and Electronic Technology, 509–513.  Huang, D.Y., & Yeo, Y.H. (2002). Robust and inaudible multi-echo audio watermarking. Proceedings of the IEEE Pacific-Rim Conference on Multimedia, 615–622.  Bender, W., Gruhl D. Echo Hiding, International Workshop on Information Hiding, 1996.

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