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An Improved Image Steganography Based On Least Significant Bit Matching Revisited (Lsbmr) Using Sobel Edge Detection

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An Improved Image Steganography Based On Least Significant Bit Matching Revisited (Lsbmr) Using Sobel Edge Detection.

ABSTRACT

Image steganography is the science of hiding data for securing confidential communication and it is the most popular type of carrier to hold information. Many algorithms have been proposed to hide information into digital images.

The least significant bit algorithm (LSB) as one of the algorithms proposed is widely used in message embedding. However, the robustness of the algorithm based on LSB is low. The hidden message is usually destroyed when some image operations like resizing, cropping and rotation are applied to the stego-image.

To overcome this limitation, this work proposed an improved image steganography based on least significant bit matching revisited (LSBMR) using Sobel edge detection that withstands image operations like resizing, rotation and cropping.

The proposed method employs 2-dimensional discrete cosine transformation (2D-DCT) to transform the detected edges of the cover image pixel value into its coefficient, embeds the secret message in the coefficients of the detected edges of the cover image which was implemented in Netbeans IDE.

INTRODUCTION

This chapter discusses the introductory part of this dissertation, which includes the background to the study, problem statements and research motivation, the research aim and objectives, research methodology, contribution to knowledge and finally the organization of the rest of the dissertation.

Recently, people exchange information using the existing communication technologies such as the internet and huge volume of data transfer takes place via the plethora of services offered by the web.

This information can be very sensitive and need to be protected against any attacker who tries to intercept them during the transmission stage.

According to Ratnakirti et al., (2013), data over internet may be stolen, intercepted, illegally modified or even destroyed by an adversary resulting in intellectual property rights infringement, data loss, data leakage and data damage.

Transmitting top secret information cannot be solely relied on the existing communication channels because the technologies are vulnerable to attacks Osama, (2005) and exchanged information can be detected relatively easily.

REFERENCES

Al-Shatanawi, O. M. and El-Emam, N. N. (2015). A New Image Steganography Algorithm Based on MLSB Method with Random Pixels Selection. International Journal of Network Security and Its Applications, 7(2), 37-53.
Allan, W. (1981). The University of Southern California-Signal and Image Processing Institute (USC-SIPI) Image Database. Retrieved May 1, 2016, from http://sipi.usc.edu/research/sipi-image-database.html.
Anderson, R. and Petitcolas, F. (1998). On the Limits of Steganography. Institute of Electrical and Electronics Engineers Journal on Selected Areas in Communication, 16(4), 474-481.
Anupam, M. and Shiladitya, P. (2015). A Novel Approach of Image Based Steganography Using Pseudorandom Sequence Generator Function and DCT Coefficients. International Journal of Computer Network and Information Security, 3(6), 42-49.
Ashok, J., Raju, Y., Munishankaraiah, S. and Srinivas, K. (2010). Steganography: An Overview. International Journal of Engineering Science and Technology, 2(10), 5985-5992.
Aubrey, D. S. (1996). Herodotus: The Histories. London: Penguin Books.
Bender, W., Gruhl, D., Morimoto, N. and Lu, A. (1996). Techniques for Data Hiding. International Business Machine Systems Journal, 35(3), 313-336.

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