5 research outputs found

    Image steganography using least significant bit and secret map techniques

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    In steganography, secret data are invisible in cover media, such as text, audio, video and image. Hence, attackers have no knowledge of the original message contained in the media or which algorithm is used to embed or extract such message. Image steganography is a branch of steganography in which secret data are hidden in host images. In this study, image steganography using least significant bit and secret map techniques is performed by applying 3D chaotic maps, namely, 3D Chebyshev and 3D logistic maps, to obtain high security. This technique is based on the concept of performing random insertion and selecting a pixel from a host image. The proposed algorithm is comprehensively evaluated on the basis of different criteria, such as correlation coefficient, information entropy, homogeneity, contrast, image, histogram, key sensitivity, hiding capacity, quality index, mean square error (MSE), peak signal-to-noise ratio (PSNR) and image fidelity. Results show that the proposed algorithm satisfies all the aforementioned criteria and is superior to other previous methods. Hence, it is efficient in hiding secret data and preserving the good visual quality of stego images. The proposed algorithm is resistant to different attacks, such as differential and statistical attacks, and yields good results in terms of key sensitivity, hiding capacity, quality index, MSE, PSNR and image fidelity

    Data hiding techniques in steganography using fibonacci sequence and knight tour algorithm

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    The foremost priority in the information and communication technology era, is achieving an efficient and accurate steganography system for hiding information. The developed system of hiding the secret message must capable of not giving any clue to the adversaries about the hidden data. In this regard, enhancing the security and capacity by maintaining the Peak Signal-to-Noise Ratio (PSNR) of the steganography system is the main issue to be addressed. This study proposed an improved for embedding secret message into an image. This newly developed method is demonstrated to increase the security and capacity to resolve the existing problems. A binary text image is used to represent the secret message instead of normal text. Three stages implementations are used to select the pixel before random embedding to select block of (64 × 64) pixels, follows by the Knight Tour algorithm to select sub-block of (8 × 8) pixels, and finally by the random pixels selection. For secret embedding, Fibonacci sequence is implemented to decomposition pixel from 8 bitplane to 12 bitplane. The proposed method is distributed over the entire image to maintain high level of security against any kind of attack. Gray images from the standard dataset (USC-SIPI) including Lena, Peppers, Baboon, and Cameraman are implemented for benchmarking. The results show good PSNR value with high capacity and these findings verified the worthiness of the proposed method. High complexities of pixels distribution and replacement of bits will ensure better security and robust imperceptibility compared to the existing systems in the literature

    Image steganography based on odd/even pixels distribution scheme and two parameters random function

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    Presently, the evolution massive of the internet gives more attention, play important role in the field of communication, and transfer messages. Nowadays, hiding sensitive or secret information inside trusted media such image without being noticed by the intruder is more needed because of the privacy cases, this method called steganography. In this paper, a method of hiding secret data in an image based on odd/even pixels distribution scheme and two parameters random function have introduced. The objective of this study is to increase the imperceptibility of proposed method with a high payload capacity of secret message. Two main process are used in the proposed method, which are embedding process and extracting process. Huffman coding technique is utilize to compress the secret message before embedding process. The security and capacity of the proposed method will increase after preparation secret message. The main objective of proposed scheme is to increase image quality (PSNR) in stego image. Two main things make the method effective: first, checking matching of secret bits with LSB and mapping to determine even and odd word during embedding, and second, segmenting the secret message to track and map every bit in stego image. Experimental results of the proposed method can achieve a high imperceptibility and robustness was emphasized

    Bit inverting map method for improved steganography scheme

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    Achieving an efficient and accurate steganography scheme for hiding information is the foremost priority in the information and communication technology era. The developed scheme of hiding the secret message must capable of not giving any clue to the adversaries about the hidden data. In this regard, enhancing the security and capacity by maintaining the Peak Signal-to-Noise Ratio (PSNR) of the steganography scheme is the main issue to be addressed. This study proposes an improved Bit Inverting Map (BIM) method and a new scheme for embedding secret message into an image. This newly developed scheme is demonstrated to increase the security and capacity to resolve the existing problems. A binary text image is used to represent the secret message instead of normal text. Three stages implementations are used to select pixels before random embedding to select block of (64 64) pixels, followed by the Knight Tour algorithm to select sub-block of (8 8) pixels, and finally by the random pixels selection. The proposed BIM is distributed over the entire image to maintain high level of security against any kind of attack. One-bit indicator is used to decide if the secret bits are inserted directly or inversely, which enhanced the complexity of embedding process. Color and gray images from the standard dataset (USC-SIPI) including Lena, Peppers, Baboon, and Cameraman are implemented for benchmarking. Self-captured images are used to test the efficacy of the proposed BIM method. The results show good PSNR values of 72.9 and these findings verified the worthiness of the proposed BIM method. High complexities of pixels distribution and replacement of bits will ensure better security and robust imperceptibility compared to the existing scheme in the literature
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