Minimizing the statistical impact of LSB steganography

  • Authors:
  • Zoran Duric;Dana Richards;Younhee Kim

  • Affiliations:
  • Department of Computer Science, George Mason University, Fairfax, VA;Department of Computer Science, George Mason University, Fairfax, VA;Department of Computer Science, George Mason University, Fairfax, VA

  • Venue:
  • ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
  • Year:
  • 2005

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Abstract

This paper explores the statistics of least-significant bit (LSB) steganography. The problem of encoding a bit sequence (message) to match the statistics of a random bit-sequence (cover) is considered. A method of hiding information in the least significant bits (LSBs) of JPEG coefficients is described; the method mimics either the chi-square statistic of JPEG coefficients or their distribution. The method uses two-bit codes to encode the message bits. It is shown to be very effective on JPEG images of natural scenes.