An Improved Image Steganography Based on Least Significant Bit Matching Revisited (LSBMR) Using Sobel Edge Detection
Chapter One
Research Aim and Objectives
The aim of this research is to develop an improved image steganography based on Least Significant Bit Matching Revisited (LSBMR) using sobel edge detection that is robust against image operations like rotation, resizing and cropping.
The objectives are to:
- carry out process analysis on image steganography techniques;
- design a modified image steganography based on LSBMR using Sobel Edge Detection;
- employ 2D-DCT transformation to the detected edges of the cover image;
- implement the proposed system;
- evaluate and compare the performance of the technique side by side the work of (Zohreh and Jihad, 2014) in relation to robustness, undetectability and
CHAPTER TWO:
LITERATURE REVIEW
The purpose of this chapter is to review the relevant concepts that are related to the research work. It takes a look at information security, overview of information hiding techniques using steganography, categories of steganography algorithms, overview of digital images used in steganography and related works on image steganography based on LSB.
Information Security
Information or data is the wealth of any organization therefore security issues are top priority to an organization dealing with confidential data (Michael and Herbert, 2011). Information security evolved from the early field of computer security and it is the protection of information assets that use, store, or transmit information from risk. The critical characteristics of information, among them confidentiality, integrity, and availability (the C.I.A. triangle), must be protected at all times; this protection is implemented by multiple measures through policies, education training and awareness, and technology.
Security is protection from danger (Webster, 1831). In other words, protection against adversaries from those who would do harm, intentionally or otherwise is the objective. National security, for example, is a multi-layered system that protects the sovereignty of a state, its assets, its resources, and its people. Achieving the appropriate level of security for an organization also requires a multifaceted system. A successful organization should have the following multiple layers of security in place to protect its operations:
- Physical security: This is to protect physical items, objects, or areas from unauthorized access and
- Personnel security: To protect the individual or group of individuals who are authorized to access the organization and its
- Operations security: This is to protect the details of a particular operation or series of activities. Communications security: To protect communications media, technology and content (Z‘aba and Maarof,2006).
- Network security: This is to protect networking components, connections, and
- Information security: This is the protection of information assets that use, store, or transmit information from risk through the application of policy, education and technology (Michael and Herbert,2011).
Information Hiding
Recently with the rapid use of information in modern technology, information hiding methods received much attention from the research community in information security. This growth of information encourages researchers to develop security techniques and to keep data transmission between sender and receiver safer from attackers (Al-Shatanawi and El-Emam, 2015). The idea of data hiding or digital steganography was first introduced with the example of prisoner‘s secret message by Simmons in 1983 according to (Subhedar and Mankar, 2014).
Information hiding refers to embedding secret message into a digital medium. The secret message can be a simple text, an image, an audio or any object that can be presented by some number of bits. It is desired to embed the secret message in an unsuspected object. This object can come in several formats such as image, audio, video, file or any other types that can carry information without destroying it. It is then referred to as cover image, cover audio, and cover video respectively. Once the secret message is embedded into the cover object it is called stego-object. After the stego-object is sent, the receiver should extract the message from the stego-object. Both the sender and receiver can agree on stego-key that is used at the extraction phase. The stego-key is used to control the hidden message from being recovered by eavesdropping. In addition, the receiver extracts the message based on the stego-key since it defines how the secret message is embedded (Subhedar and Mankar, 2014).
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CHAPTER THREE:
PROPOSED DESIGN OF IMAGE STEGANOGRAPHY BASED ON LSBMR USING SOBEL EDGE DETECTION
This part of the research presents the methods applied in our research in order to achieve the stated objectives. First part provides the readers with an opportunity to know about the approach of the study and the reasons behind the selection of the research method. Also, it presents the algorithm of the improved image steganography based on LSBMR using Sobel edge detection.
- Improved Image Steganography based on LSBMR using Sobel Edge Detection The improved image steganography based on LSBMR using Sobel Operator uses Sobel‘s edge detection technique to get edges and transform the detected edges into its co-efficient using 2D-DCT. These coefficients are manipulated for embedding purpose. For lower embedding rates the middle frequencies are used for holding information. The goal of this method is to preserve the statistical and visual features of the cover image and obtain a stego-image that is robust against image operations such as rotation, resizing and cropping. Selecting units for data hiding depends on the secret message and the co-efficient of the cover image content. Thus, the new technique is to provide better resistance against steganalysis process and image
The next section described the details of the method.
Proposed System Flow Diagram
The flow diagram of the system is depicted in Figure 3.1. Figure 3.1(a) shows schema of the message hiding and (b) extraction process in parts. Figure 3.2 shows the combined detailed block system for message hiding and extraction process both on sender and receiver side.
CHAPTER FOUR:
IMPLEMENTATION, RESULTS AND ANALYSIS
This chapter provides the proposed system implementation with screenshots for hiding and extracting secret messages. The system provides easy to use interface. It also presents all the experiments conducted to evaluate the proposed system and results of the comparative analysis obtained from the research.
CHAPTER FIVE:
SUMMARY, CONCLUSION AND RECOMMENDATION
Summary
In this dissertation, Improved Image Steganography based on LSBMR Using Sobel Edge Detection was designed. Although there have been many researches on image steganography, most of the existing algorithms have high embedding capacities, but they are vulnerable to small modifications that may result from image processing operations such as cropping, rotation, scaling and resizing. The improved system was designed with the objective of improving the robustness of the technique to work in transform domain so that the stego-images do not suffer any act of image manipulations. The proposed system was implemented and evaluated using image steganography performance metrics and statistical steganalysis technique and the results proved to be robust than the base technique that was extended.
Conclusion
In line with the objectives of the research, the following has been achieved.
- An Improved Image Steganography Based on LSBMR using Sobel Edge Detection has been
- The proposed technique employs image transformation technique specifically 2D-DCT to detected edges of the cover image to provide a better stego-image that can withstand image operations such as cropping, resizing and
- This technique was successfully implemented in Java and Netbeans IDE
- Experimental results conducted showed that the proposed technique produced better stego-imagequality that can withstand multiple image operations such as rotation, resizing
and cropping in relation to robustness and PSNR of 68dB for 8000 bits of secret message with regards to the invisibility.
Recommendation
This section presents some suggestion to extend the technique.
- The method can achieve its minimal time of processing by reducing the compression process to have lower time
- Furthermore, future research should focus on applying the Improved Image Steganography based on LSBMR using Sobel edge detection on higher bit order instead of the least significant
- Finally, the proposed technique was applied on colour images. Thus, it is suggested to extend it to be used on other steganographic cover objects such as video or audio. For example, the Improved Image Steganography based on LSBMR using Sobel edge detection can be applied on frames of the cover video. Then extensive evaluation should be then conducted to witness the effectiveness of the technique on video
Research Contributions to Knowledge
The main contributions of this work are in two phases:
- An improved image steganography system based on LSBMR using Sobel edge detection that is robust and works in transform domain was
- The experimental results of this research produced better stego-image quality that can withstand multiple image operations such as rotation, resizing and cropping in relation to robustness and PSNR of 68dB for 8000 bits of secret message as regards to the
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.
