Journal of Intelligent Systems (Dec 2014)
Data Hiding Based on Improved Exploiting Modification Direction Method and Huffman Coding
Abstract
The rapid growth of covert activities via communications network brought about an increasing need to provide an efficient method for data hiding to protect secret information from malicious attacks. One of the options is to combine two approaches, namely steganography and compression. However, its performance heavily relies on three major factors, payload, imperceptibility, and robustness, which are always in trade-offs. Thus, this study aims to hide a large amount of secret message inside a grayscale host image without sacrificing its quality and robustness. To realize the goal, a new two-tier data hiding technique is proposed that integrates an improved exploiting modification direction (EMD) method and Huffman coding. First, a secret message of an arbitrary plain text of characters is compressed and transformed into streams of bits; each character is compressed into a maximum of 5 bits per stream. The stream is then divided into two parts of different sizes of 3 and 2 bits. Subsequently, each part is transformed into its decimal value, which serves as a secret code. Second, a cover image is partitioned into groups of 5 pixels based on the original EMD method. Then, an enhancement is introduced by dividing the group into two parts, namely k1 and k2, which consist of 3 and 2 pixels, respectively. Furthermore, several groups are randomly selected for embedding purposes to increase the security. Then, for each selected group, each part is embedded with its corresponding secret code by modifying one grayscale value at most to hide the code in a (2ki + 1)-ary notational system. The process is repeated until a stego-image is eventually produced. Finally, the χ2 test, which is considered one of the most severe attacks, is applied against the stego-image to evaluate the performance of the proposed method in terms of its robustness. The test revealed that the proposed method is more robust than both least significant bit embedding and the original EMD. Additionally, in terms of imperceptibility and capacity, the experimental results have also shown that the proposed method outperformed both the well-known methods, namely original EMD and optimized EMD, with a peak signal-to-noise ratio of 55.92 dB and payload of 52,428 bytes.
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