An Improved Image Steganography Based on Least Significant Bit Matching Revisited LSBMR Using Sobel Edge Detection

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

Project / Seminar Material
Reference ID: PS-5585-TM

DEDICATION

This research material titled “An Improved Image Steganography Based on Least Significant Bit Matching Revisited (LSBMR) Using Sobel Edge Detection” is dedicated to God for his enabling grace, and to all computer enthusiasts who contributed to make life a pleasant experience during my research documentation.

ACKNOWLEDGEMENT

I extend my sincere gratitude to all those who contributed to the completion of this project. Special thanks to my Supervisor (Name of your Supervisor), the Head of Department (Name of your HOD), the Lecturers in the department of Computer Science Education, Book Authors and Profound Scholars of existing or related project material on “An Improved Image Steganography Based on Least Significant Bit Matching Revisited (LSBMR) Using Sobel Edge Detection” for their invaluable guidance, support, and expertise throughout the journey.

I am also grateful to your study area (mention any funding organizations, if applicable) for their financial assistance. This research would not have been possible without the encouragement and assistance of some stakeholders (mention any mentors, teachers, or colleagues). Additionally, I would like to acknowledge the understanding and patience of my family and friends during this endeavor. Your unwavering support has been a constant source of motivation. Thank you all for being part of this meaningful endeavor.

TABLE OF CONTENTS

PRELIMINARY PAGES

CHAPTER ONE

INTRODUCTION

    CHAPTER TWO

    LITERATURE REVIEW

    • 2.1 Introduction
    • 2.2 Conceptual Review
    • 2.3 Theoretical Framework
    • ⋮
    • 2.4 Empirical Studies

    CHAPTER THREE

    RESEARCH METHODOLOGY

    • 3.1 Introduction
    • 3.2 Research Design
    • 3.3 Population of Study
    • 3.4 Sampling and Sampling Technique
    • 3.5 Validation of Research Instrument
    • 3.6 Method of Data Collection
    • 3.7 Method of Data Analysis
    • 3.8 Questionnaire Administration
    • 3.9 Ethical Consideration
    • 3.10 Statistical Analysis

    CHAPTER FOUR

    DATA ANALYSIS, RESULT AND DISCUSSION

    • 4.1 Introduction
    • 4.2 Presentation and Analysis of Data
    • 4.3 Re-statement of Research Questions
    • 4.4 Test of Hypotheses
    • 4.5 Discussion of Findings

    CHAPTER FIVE

    SUMMARY, CONCLUSION AND RECOMMENDATION

    • 5.1 Introduction
    • 5.2 Summary of Findings
    • 5.3 Conclusion
    • 5.4 Recommendation
    • 5.5 Suggestion for Further Study

    REFERENCES

    APPENDIX A - “QUESTIONNAIRE”

    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. Experimental results produced better stego-image quality that is robust against multiple image operations such as resizing and cropping. The statistical steganalysis tools such as Virtual Steganographic Laboratory (VSL) and StegExpose cannot detect the presence of secret information in the stego-image. Also, the proposed system generated stego-image with Peak Signal to Noise Ratio (PSNR) that is an image quality metric of 68 decibels (dB) for 8000 bits of secret message as regards to the invisibility over the existing steganography technique.

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

    CHAPTER ONE

    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.

    1.1 Background to the Study

    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. Therefore, it is vital to protect the privacy and confidentiality of top secret message during its transit through the internet. To preserve the privacy and confidentiality of important data over the internet it must be provided with a metaphorical envelope such that its contents are revealed only to the intended receiver Ratnakirti et al., (2013) without arousing suspicions. Data hiding techniques such as steganography precisely aim at performing this task.

    The steganography technique has been used many years ago to convey secret messages. For instance, Greek historian Herodotus was the first to document the usage of steganography to send messages (Aubrey, 1996). A slave was sent by his master to deliver a secret message tattooed on his scalp. After the message was tattooed, the slave waited until his hair grew back and concealed the message. The most popular steganographic methods between the 13th and 16th century involved written text. One method used a mask, a paper with holes, shared between the sender and recipient. The mask was simply put over the text and the message was revealed. Francis Bacon realized that two different fonts for each letter can be applied to embed binary representations of messages. Holub, (2014), stated that ”•Brewster devised a very original technique in 1857, which was later used in several wars”–.

    …

    CHAPTER TWO

    2.0 Literature Review

    2.1 Introduction

    This chapter focuses on the review of related literature. A literature review includes the current knowledge as well as theoretical and methodological contributions to a particular topic. It documents the state of the art with respect to the topic you are writing. It surveys the literature in the topic selected. In this research work the literature review includes the …

    Summary Headlines for An Improved Image Steganography Based on Least Significant Bit Matching Revisited (LSBMR) Using Sobel Edge Detection