Srabani Khan

Bio: Srabani Khan is an academic researcher from Academy of Technology. The author has contributed to research in topics: Encryption & Steganography. The author has an hindex of 2, co-authored 2 publications receiving 81 citations.

Image encryption using affine transform and XOR operation

Abstract: Image encryption is a suitable method to protect image data. Image and text data has their unique features. The available encryption algorithms are good for text data. They may not be suitable for multimedia data. In fact the pixels of natural images are highly correlated to their neighboring pixels. Due to this strong correlation any pixel can be practically predicted from the values of its neighbors. In this article, we propose a new location transformation based encryption technique. We redistribute the pixel values to different location using affine transform technique with four 8-bit keys. The transformed image then divided into 2 pixels × 2 pixels blocks and each block is encrypted using XOR operation by four 8-bit keys. The total key size used in our algorithm is 64 bit which proves to be strong enough. The experimental results proved that after the affine transform the correlation between pixel values was significantly decreased.

A Weighted Location Based LSB Image Steganography Technique

Abstract: Steganography is the art of hiding the presence of communication by embedding secret messages into innocent, innocuous looking cover documents, such as digital images, videos, sound files. We present here a novel steganographic method based on affine cipher encryption algorithm and the least significant bit (LSB) substitution in order to provide a strong security and imperceptible visual quality to secret message. We encrypt the 8 bit secret image by changing pixel values using affine cipher. After that each 8 bit pixel of encrypted secret image is divided into 4 groups of 2 bit each. Each part which have a decimal value between 0 to 3 determines the location in each pixel of cover image where to embed the message. We do not store the actual secret message instead we encode the secret message into cover image using the value of each group of secret message. Since, we have two layers of encoding: one using private keys of affine cipher and other for steganography, our methods proves to be more secure than others. Our experimental results also proves that the proposed method has got an acceptable image quality as supported by PSNR values.

Quantum image Gray-code and bit-plane scrambling

Abstract: With the rapid development of multimedia technology, the image scrambling for information hiding and digital watermarking is crucial. But, in quantum image processing field, the study on image scrambling is still few. Several quantum image scrambling schemes are basically position space scrambling strategies; however, the quantum image scrambling focused on the color space does not exist. Therefore, in this paper, the quantum image Gray-code and bit-plane (GB) scrambling scheme, an entire color space scrambling strategy, is proposed boldly. On the strength of a quantum image representation NEQR, several different quantum scrambling methods using GB knowledge are designed. Not only can they change the histogram distribution of the image dramatically, some designed schemes can almost make the image histogram flush, enhance the anti-attack ability of digital image, but also their cost or complexity is very low. The simulation experiments result also shows a good performance and indicates the particular advantage of GB scrambling in quantum image processing field.

A Content-Adaptive Joint Image Compression and Encryption Scheme

Abstract: For joint image compression and encryption schemes, the encryption power and compression efficiency are commonly two contradictory things. In this paper, we propose a new joint image compression and encryption scheme based on a lossy JPEG standard, which aims at encryption power's enhancement, on the premise of maintaining the JPEG's compression efficiency. The proposed scheme is image-content-adaptive, since the secret encryption key is generated from the plain image using the BLAKE2 hash algorithm. Three encryption operations are contained in our scheme, alternating new orthogonal transforms transformation, dc coefficients encryption, and ac coefficients encryption. To save the cost for transmitting different encryption keys each time to decoder for decryption when the plain image changes, we propose embedding the encryption key into the entropy-encoded bitstream of some ac coefficients, and the whole embedding procedure is controlled by another secret key called the embedding key. Extensive experiments are conducted to show that our encryption scheme is JPEG friendly, and has good confusion and diffusion properties. Detailed security analysis is also given to illustrate the proposed scheme's persistence to various cryptanalysis strategies.

A pixel permutation based image encryption technique using chaotic map

Abstract: In the last decade, with a rapid increase in multimedia productions, image encryption has become a significant part of information security. The inherent image features make image encryption different from text encryption and also makes it difficult to encrypt images using the traditional encryption techniques. This paper presents an overview of the different encryption algorithms in details, analyzing its effect in the field of image cryptography. The paper further discusses the role of chaos theory in the field of image encryption and makes use of the chaos theory to propose an image encryption technique that is based on pixel permutation. Existing image encryption techniques produce encrypted images that resemble a texture or noise like image increasing the chance of attack as it becomes perceivable as an encrypted image. The proposed image encryption technique produces an encrypted image and masquerades it with any general image, hence eluding the attacker. The proposed algorithm is also compared with the Arnold’s cat map algorithm visually as well as statistically using the evaluation metrics Structural Similarity Index (SSIM), Correlation coefficient (CC) and Number of changing Pixel Rate (NPCR).