Enhanced LSB Image Steganography Method By Using Knight Tour Algorithm, Vigenere Encryption and LZW Compression
The challenge of steganographic methods is to create a rational balance between the quality of the file and the size of data that can be transferred. In addition, the robustness of the technique and security of the obscure data are the facts that cannot be dissembled. The Least Significant Bit (LSB) insertion approach provides a high degree of visual quality and a large amount of capacity for the concealed data, but the covert message is not well protected in this method. In the proposed method, the secret data is firstly encoded by using the Vigenere encryption method to guarantee the protection of the hidden message. Afterward, the Lempel Ziv Welch (LZW) technique compresses the data to reduce the occupational capacity of the confidential data. Then, by utilizing the extended knight tour algorithm, each bitstream of the data is spread out on the image to increase the robustness of the method. The results show that the proposed method not only improves the security and payload capacity problems of the simple LSB method, but also increases the visual quality of the stego image.
Keywords: Steganography, LSB embedding technique, Knight Tour algorithm, Vigenere encryption, LZW compression
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ABOUT THE AUTHORS
Morteza Bashardoost
Morteza Bashardoost received his bachelor\'s degree of software engineering from Islamic Azad University,Lahijan,Iran in 2005. Afterward, he obtained his master of computer science from Universiti Teknologi Malaysia (UTM),Johor, Malaysia in 2012. He is currently a Phd student of computer science in Universiti Teknologi Malaysia. His areas of research interest include digital image processing, pattern recognition, face recognition, image steganography and watermarking.
Ghazali Bin Sulong
Ghazali Bin Sulong received his Ph.D. and M.Sc. degrees in computing from University of Wales, Cardiff, United Kingdom in 1989 and 1982 respectively, and B.Sc. degree in statistic from National University of Malaysia (UKM), in 1979. Currently, he is a professor and principle researcher in image processing in Universiti Teknologi Malaysia (UTM).
Parisa Gerami
Parisa Gerami studied computer science in Zarandieh Institute of Higher education (B.Sc) in 2009 and received her master degree from university technology Malaysia in computer science (information security) in 2012. Her research interests are Image Processing, Computer Vision, Cryptography, Steganography, Watermarking, Security, Networking Security, Wireless Sensor Network and Wireless Multimedia Sensor Network.
Morteza Bashardoost
Morteza Bashardoost received his bachelor\'s degree of software engineering from Islamic Azad University,Lahijan,Iran in 2005. Afterward, he obtained his master of computer science from Universiti Teknologi Malaysia (UTM),Johor, Malaysia in 2012. He is currently a Phd student of computer science in Universiti Teknologi Malaysia. His areas of research interest include digital image processing, pattern recognition, face recognition, image steganography and watermarking.
Ghazali Bin Sulong
Ghazali Bin Sulong received his Ph.D. and M.Sc. degrees in computing from University of Wales, Cardiff, United Kingdom in 1989 and 1982 respectively, and B.Sc. degree in statistic from National University of Malaysia (UKM), in 1979. Currently, he is a professor and principle researcher in image processing in Universiti Teknologi Malaysia (UTM).
Parisa Gerami
Parisa Gerami studied computer science in Zarandieh Institute of Higher education (B.Sc) in 2009 and received her master degree from university technology Malaysia in computer science (information security) in 2012. Her research interests are Image Processing, Computer Vision, Cryptography, Steganography, Watermarking, Security, Networking Security, Wireless Sensor Network and Wireless Multimedia Sensor Network.
