145 research outputs found
Hybrid chaos-based image encryption algorithm using Chebyshev chaotic map with deoxyribonucleic acid sequence and its performance evaluation
The media content shared on the internet has increased tremendously nowadays. The streaming service has major role in contributing to internet traffic all over the world. As the major content shared are in the form of images and rapid increase in computing power a better and complex encryption standard is needed to protect this data from being leaked to unauthorized person. Our proposed system makes use of chaotic maps, deoxyribonucleic acid (DNA) coding and ribonucleic acid (RNA) coding technique to encrypt the image. As videos are nothing but collection of images played at the rate of minimum 30 frames/images per second, this methodology can also be used to encrypt videos. The complexity and dynamic nature of chaotic systems makes decryption of content by unauthorized personal difficult. The hybrid usage of chaotic systems along with DNA and RNA sequencing improves the encryption efficiency of the algorithm and also makes it possible to decrypt the images at the same time without consuming too much of computation power
A novel conservative chaos driven dynamic DNA coding for image encryption
In this paper, we propose a novel conservative chaotic standard map-driven
dynamic DNA coding (encoding, addition, subtraction and decoding) for the image
encryption. The proposed image encryption algorithm is a dynamic DNA coding
algorithm i.e., for the encryption of each pixel different rules for encoding,
addition/subtraction, decoding etc. are randomly selected based on the
pseudorandom sequences generated with the help of the conservative chaotic
standard map. We propose a novel way to generate pseudo-random sequences
through the conservative chaotic standard map and also test them rigorously
through the most stringent test suite of pseudo-randomness, the NIST test
suite, before using them in the proposed image encryption algorithm. Our image
encryption algorithm incorporates a unique feed-forward and feedback mechanisms
to generate and modify the dynamic one-time pixels that are further used for
the encryption of each pixel of the plain image, therefore, bringing in the
desired sensitivity on plaintext as well as ciphertext. All the controlling
pseudorandom sequences used in the algorithm are generated for a different
value of the parameter (part of the secret key) with inter-dependency through
the iterates of the chaotic map (in the generation process) and therefore
possess extreme key sensitivity too. The performance and security analysis has
been executed extensively through histogram analysis, correlation analysis,
information entropy analysis, DNA sequence-based analysis, perceptual quality
analysis, key sensitivity analysis, plaintext sensitivity analysis, etc., The
results are promising and prove the robustness of the algorithm against various
common cryptanalytic attacks.Comment: 29 pages, 5 figures, 15 table
Color Image Encryption Using LFSR, DNA, and 3D Chaotic Maps
One of the most important challenges facing researchers is to find new methods to protect data sent over the Internet and prevent unauthorized access to it. In this paper, we present a new method for encrypting image data divided into two stages. The first stage requires redistributing the positions of the pixels by using a key of random numbers generated by linear feedback shift registers and then encrypting the data using deoxyribonucleic acid rules. The data generated in the previous stage is encrypted again using chaotic maps to increase the level of security in the second stage. Several statistical tests were implemented to verify the efficiency of the proposed method and compare the results with the work of other researchers. The results of the tests proved a reasonable safety rate compared to other techniques
Image Encryption Algorithm Based on DNA Encoding and Chaotic Maps
We propose a new image encryption algorithm based on DNA sequences combined with chaotic maps. This algorithm has two innovations: (1) it diffuses the pixels by transforming the nucleotides into corresponding base pairs a random number of times and (2) it confuses the pixels by a chaotic index based on a chaotic map. For any size of the original grayscale image, the rows and columns are fist exchanged by the arrays generated by a logistic chaotic map. Secondly, each pixel that has been confused is encoded into four nucleotides according to the DNA coding. Thirdly, each nucleotide is transformed into the corresponding base pair a random number of time(s) by a series of iterative computations based on Chebyshev’s chaotic map. Experimental results indicate that the key account of this algorithm is 1.536 × 10127, the correlation coefficient of a 256 × 256 Lena image between, before, and after the encryption processes was 0.0028, and the information entropy of the encrypted image was 7.9854. These simulation results and security analysis show that the proposed algorithm not only has good encryption effect, but also has the ability to repel exhaustive, statistical, differential, and noise attacks
A DNA Based Colour Image Encryption Scheme Using A Convolutional Autoencoder
With the advancement in technology, digital images can easily be transmitted
and stored over the Internet. Encryption is used to avoid illegal interception
of digital images. Encrypting large-sized colour images in their original
dimension generally results in low encryption/decryption speed along with
exerting a burden on the limited bandwidth of the transmission channel. To
address the aforementioned issues, a new encryption scheme for colour images
employing convolutional autoencoder, DNA and chaos is presented in this paper.
The proposed scheme has two main modules, the dimensionality conversion module
using the proposed convolutional autoencoder, and the encryption/decryption
module using DNA and chaos. The dimension of the input colour image is first
reduced from N M 3 to P Q gray-scale image using the
encoder. Encryption and decryption are then performed in the reduced dimension
space. The decrypted gray-scale image is upsampled to obtain the original
colour image having dimension N M 3. The training and
validation accuracy of the proposed autoencoder is 97% and 95%, respectively.
Once the autoencoder is trained, it can be used to reduce and subsequently
increase the dimension of any arbitrary input colour image. The efficacy of the
designed autoencoder has been demonstrated by the successful reconstruction of
the compressed image into the original colour image with negligible perceptual
distortion. The second major contribution presented in this paper is an image
encryption scheme using DNA along with multiple chaotic sequences and
substitution boxes. The security of the proposed image encryption algorithm has
been gauged using several evaluation parameters, such as histogram of the
cipher image, entropy, NPCR, UACI, key sensitivity, contrast, etc. encryption
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