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Proceedings ArticleDOI

Image Encryption Using Legendre Sequence and DCT

TL;DR: The proposed algorithm using Legendre PN sequence which is based on prime numbers, an image encryption technique has been proposed in this paper, proving that changes made to cover image is very less and Identification of key to decrypt the original image is impossible to detect.
Abstract: One of the fears in the field of communication is insecurity of data. Pseudo random noise (PRN), which is similar to noise and also fulfills a greater number of the standard tests for statistical randomness, can be used as a key for encryption. Using Legendre PN sequence which is based on prime numbers, an image encryption technique has been proposed in this paper. Based on the number of pixels in the image, Legendre sequences are generated for a set of prime numbers and concatenated to generate the required length sequence. This sequence is then used to encrypt the secret image that generates noise like pattern. This encrypted image is later embedded into a larger image using DCT technique to have double security. The proposed algorithm using Legendre sequence when tested on various images has always produced a PSNR value of cover image above 20, proving that changes made to cover image is very less. Identification of key to decrypt the original image is impossible to detect as multiple Legendre sequences are used to form PN sequence. Steganography with DCT adds to improvement in security. The above algorithm can be extended to color images and the robustness of the algorithm can be tested using different attacking methods.
References
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Journal ArticleDOI
TL;DR: The linear complexity of all Legendre sequences and the (monic) feedback polynomial of the shortest linear feedback shift register that generates such a Legendre sequence are determined.
Abstract: We determine the linear complexity of all Legendre sequences and the (monic) feedback polynomial of the shortest linear feedback shift register that generates such a Legendre sequence. The result shows that Legendre sequences are quite good from the linear complexity viewpoint.

175 citations


"Image Encryption Using Legendre Seq..." refers methods in this paper

  • ...When a binary sequence is a Pseudo Random Binary Sequence (PRBS) it is characterized by it’s even and odd auto correlation function (ACF) given by: ACFe( ) = ∑ !"# $% (5) ACFo( ) = ∑ − !" "# $% ∑ !"# $!" (6) where ‘&’ is the time shift of the sequence ranging from 0 to p-1....

    [...]

Proceedings ArticleDOI
27 Sep 2013
TL;DR: This work is concerned with implementing Steganography for images, with an improvement in both security and image quality, and shows good enhancement to Least Significant Bit technique in consideration to security as well as image quality.
Abstract: This work is concerned with implementing Steganography for images, with an improvement in both security and image quality. The one that is implemented here is a variation of plain LSB (Least Significant Bit) algorithm. The stego-image quality is improved by using bit-inversion technique. In this technique, certain least significant bits of cover image are inverted after LSB steganography that co-occur with some pattern of other bits and that reduces the number of modified LSBs. Thus, less number of least significant bits of cover image is altered in comparison to plain LSB method, improving the PSNR of stegoimage. By storing the bit patterns for which LSBs are inverted, message image can be obtained correctly. To improve the robustness of steganography, RC4 algorithm has been used to achieve the randomization in hiding message image bits into cover image pixels instead of storing them sequentially. This process randomly disperses the bits of the message in the cover image and thus, making it harder for unauthorized people to extract the original message. The proposed method shows good enhancement to Least Significant Bit technique in consideration to security as well as image quality.

97 citations

Proceedings ArticleDOI
30 Mar 2012
TL;DR: This paper presents a novel technique for image steganography based on Huffman Encoding that has a high capacity and a good invisibility, and Peak Signal to Noise Ratio (PSNR) of stego image with cover image shows better result in comparison with other existing Steganography approaches.
Abstract: Steganography is the science that involves communicating secret data in an appropriate multimedia carrier, e.g., image, audio and video files. It comes under the assumption that if the feature is visible, the point of attack is evident, thus the goal here is always to conceal the very existence of the embedded data. This paper presents a novel technique for image steganography based on Huffman Encoding. Two 8 bit gray level image of size M X N and P X Q are used as cover image and secret image respectively. Huffman Encoding is performed over the secret image/message before embedding and each bit of Huffman code of secret image/message is embedded inside the cover image by altering the least significant bit (LSB) of each of the pixel's intensities of cover image. The size of the Huffman encoded bit stream and Huffman Table are also embedded inside the cover image, so that the Stego-Image becomes standalone information to the receiver. The experimental result shows that the algorithm has a high capacity and a good invisibility. Moreover Peak Signal to Noise Ratio (PSNR) of stego image with cover image shows better result in comparison with other existing steganography approaches. Furthermore, satisfactory security is maintained since the secret message/image cannot be extracted without knowing the decoding rules and Huffman table.

79 citations

01 Jan 2011
TL;DR: A chaos- based encryption algorithm for images based on pixel scrambling where the position of the data is scrambled in the order of randomness of the elements obtained from the chaotic map and again rearranged back to their original position in decryption process.
Abstract: The advent of wireless communications, both inside and outside the home-office envi- ronment has led to an increased demand for effective encryption systems. The beauty of encryp- tion technology comes out in more pronounced way when there is no absolute relation between cipher and original data and it is possible to rebuild the original image in much easier way. As chaotic systems are known to be more random and non-predictable, they can be made utilized in achieving the encryption. The transposition technology of encryption systems requires scramble- ness behaviour in order to achieve the encryption of the data. This scrambleness behaviour can be derived from the randomness property of chaos which can be better utilized in the techniques like transposition system. In wireless communication systems, bandwidth utilization is an impor- tant criterion. In order to use encryption system in wireless communication; key space plays an important role for the efficient utilization of the bandwidth. In this paper we present a chaos- based encryption algorithm for images. This algorithm is based on pixel scrambling where in the randomness of the chaos is made utilized to scramble the position of the data. The position of the data is scrambled in the order of randomness of the elements obtained from the chaotic map and again rearranged back to their original position in decryption process. The same algoritm is tested with two different maps and performance analysis is done to select best suited map for en- cription.

49 citations

Journal ArticleDOI
TL;DR: In this paper, a Legendre sequence of period p for any odd prime p is explicitely represented as a sum of trace functions from GF(2n) toGF(2), where n is the order of 2 mod p.
Abstract: In this paper, a Legendre sequence of period p for any odd prime p is explicitely represented as a sum of trace functions from GF(2^n) to GF(2), where n is the order of 2 mod p.

39 citations


"Image Encryption Using Legendre Seq..." refers methods in this paper

  • ...When a binary sequence is a Pseudo Random Binary Sequence (PRBS) it is characterized by it’s even and odd auto correlation function (ACF) given by: ACFe( ) = ∑ !"# $% (5) ACFo( ) = ∑ − !" "# $% ∑ !"# $!" (6) where ‘&’ is the time shift of the sequence ranging from 0 to p-1....

    [...]