Kamau, Gabriel Macharia (2013) An Enhanced Least Significant Bit Steganographic Method for Information Hiding. Masters thesis, Jomo Kenyatta University of Agriculture & Technology.
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PDF (An Enhanced Least Significant Bit Steganographic Method for Information Hiding)
Kamau, Gabriel Macharia Kamau- MSc. Software Engineering- 2013.pdf - Accepted Version Restricted to Repository staff only Download (3MB) | Request a copy |
Abstract
The least significant bit (LSB) insertion method is a simple steganographic algorithm that takes the least significant bit in some bytes of the cover medium and swaps them with a sequence of bytes containing the secret data in order to conceal the information in the cover medium. However its imperceptibility and hiding capacity are relatively low. This is as revealed by the statistical characteristics of its resultant stego images compared to the original cover images. To increase the level of imperceptibility and the hiding capacity in the LSB insertion method, this research proposes an enhanced LSB method that employs a selective and randomized approach in picking specific number of target image bits to swap with the secret data bits during the embedding process. To facilitate the selective picking of the target image bits, a variation of the standard minimal linear congruential pseudo random number generator (LCG) is used. The message digest (digital signature) of a user supplied password is used to seed the LCG and to extract the message from the cover medium. In measuring the effectiveness of the proposed method, the study adopted an experimental research design where the statistical characteristics of the proposed method stego images were compared with those of the traditional LSB method in a comparative experiment designed to establish the levels of image distortion (noise) introduced in the original cover image when either of the methods is used under the same payload and image. The experiment results indicated improved levels of imperceptibility and hiding capacity in the proposed method.
| Item Type: | Thesis (Masters) |
|---|---|
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Africana |
| Depositing User: | Geoffrey Obatsa |
| Date Deposited: | 27 Apr 2017 10:39 |
| Last Modified: | 27 Apr 2017 10:39 |
| URI: | http://thesisbank.jhia.ac.ke/id/eprint/1530 |
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