Shihua Zhou

Image Encryption Algorithm Based on DNA Sequences for the Big Image

With the fast development of Internet technology and informationprocessing technology, the image is commonly transmitted via theInternet. People enjoy the convenience and shortcut, but people haveto face to the obsession that the important image information intransmission is easily intercepted by unknown persons or hackers. Inorder to enhance the image information security, image encryptionbecomes an important research direction. An image encryptionalgorithm based on DNA sequences for the big image is presented inthis paper. The main purpose of this algorithm is to reduce the bigimage encryption time. This algorithm is implemented by using thenatural DNA sequences as main keys. The first part is the process ofpixel scrambling. The original image is confused in the light of thescrambling sequence is generated by the DNA sequence. The secondpart is the process of pixel replacement. The pixel gray values ofthe new image and the one of the three encryption templates aregenerated by the other DNA sequence are XORed bit-by-bit in turn.The experimental result demonstrates that the image encryptionalgorithm is feasible and simple. Through performance analysis, thisalgorithm is robust against all kinds of attacks and owns highersecurity.

A Summarization on Image Encryption

Abstract With the fast development of the computer technology and information processing technology, the problem of information security is becoming more and more important. Information hiding is usually used to protect the important information from disclosing when it is transmitting over an insecure channel. Digital image encryption is one of the most important methods of image information hiding and camouflage. The image encryption techniques mainly include compression methodology, modern cryptography mechanism, chaos techniques, DNA techniques, and so on. In this paper, we summarize the main encryption algorithms and classify them based on the means. In particular, chaos-based and DNA cryptography-based image encryption algorithms are illustrated and analyzed in detail. Finally, the future direction in this field is discussed.

An image encryption algorithm based on DNA self-assembly technology

DNA self-assembly that is fast developed in the fields of DNA computing and nano technology has become the focus of scientific fields. DNA self-assembly is a method that uses the characteristics of base-pair to form polyhedron or super molecular structure. This is a complex progress from disordered to well-ordered, from simple to complicated. This paper mainly introduces that the DNA self-assembly technology is applied into the image encryption. In this paper, we proposed a complete design scheme of DNA tiles that is suitable for the image encryption. The DNA tiles mainly include five types, namely DNA tiles of the plaintext, DNA tiles of the encryption, DNA tiles of the cipertext, DNA tiles of the key and DNA tiles of the decryption. Through a simulate example, the effect of the image encryption algorithm is shown.

Constructing DNA Barcode Sets Based on Particle Swarm Optimization

Following the completion of the human genome project, a large amount of high-throughput bio-data was generated. To analyze these data, massively parallel sequencing, namely next-generation sequencing, was rapidly developed. DNA barcodes are used to identify the ownership between sequences and samples when they are attached at the beginning or end of sequencing reads. Constructing DNA barcode sets provides the candidate DNA barcodes for this application. To increase the accuracy of DNA barcode sets, a particle swarm optimization (PSO) algorithm has been modified and used to construct the DNA barcode sets in this paper. Compared with the extant results, some lower bounds of DNA barcode sets are improved. The results show that the proposed algorithm is effective in constructing DNA barcode sets.

Correcting Errors in Image Encryption Based on DNA Coding

As a primary method, image encryption is widely used to protect the security of image information. In recent years, image encryption pays attention to the combination with DNA computing. In this work, we propose a novel method to correct errors in image encryption, which results from the uncertainty of DNA computing. DNA coding is the key step for DNA computing that could decrease the similarity of DNA sequences in DNA computing as well as correct errors from the process of image encryption and decryption. The experimental results show our method could be used to correct errors in image encryption based on DNA coding.

Splicing Model and Hyper–Chaotic System for Image Encryption

Abstract Encryption is an effective way to protect the image information from attacking by intruders in the transmission applications through the Internet. This study presents an image encryption scheme on the basics of the formal model of DNA computing-splicing system and hyper-chaotic system, which utilizes the instinct properties of hyper-chaotic system and splicing model while programming the method. In our proposed algorithm, the quaternary coding is used to split the plain image into four sub-sections so that we can’t get the cipher image without any one sub-section. This new method can be used to change the plain image information drastically. The experimental results and security analysis show that our method not only has a good security but also increases the resistance to common attacks such as exhaustive attacks, statistical attacks and differential attacks.

An Image Encryption Scheme Based on DNA Computing and Cellular Automata

Networks have developed very quickly, allowing the speedy transfer of image information through Internet. However, the openness of these networks poses a serious threat to the security of image information. The field of image encryption has drawn attention for this reason. In this paper, the concepts of 1-dimensional DNA cellular automata and T-DNA cellular automata are defined, and the concept of reversible T-DNA cellular automata is introduced. An efficient approach to encryption involving reversible T-DNA cellular automata as an encryption tool and natural DNA sequences as the main keys is here proposed. The results of a simulation experiment, performance analysis, and comparison to other encryption algorithms showed this algorithm to be capable of resisting brute force attacks, statistical attacks, and differential attacks. It also enlarged the key space enormously. It meets the criteria for one-time pad and resolves the problem that one-time pad is difficult to save.

Reversible Data Hiding Based on DNA Computing

Biocomputing, especially DNA, computing has got great development. It is widely used in information security. In this paper, a novel algorithm of reversible data hiding based on DNA computing is proposed. Inspired by the algorithm of histogram modification, which is a classical algorithm for reversible data hiding, we combine it with DNA computing to realize this algorithm based on biological technology. Compared with previous results, our experimental results have significantly improved the ER (Embedding Rate). Furthermore, some PSNR (peak signal-to-noise ratios) of test images are also improved. Experimental results show that it is suitable for protecting the copyright of cover image in DNA-based information security.

Digital watermarking based on chaos game representation and discrete cosine transform

Digital watermarking is a means to protect multimedia copyright, and it will be subjected to various attacks. Therefore, the research on the robustness of watermarking algorithm is considered as a hot field. A digital image watermarking algorithm that can resist geometric attacks is proposed based on chaos game representation and normalization. Firstly, the original image is mapped to the geometrically invariant space using the image normalization. Then, according to the image characteristics and the human visual characteristics, the valid image is transformed by DCT transform and the embedding number is determined. At last, the embedding image and position are determined by chaos game representation and the embedding number, and the watermarking is embedded in the light of the embedding number and position into the embedding image. Analyzing experimental results, we can know that the algorithm is invisible, secure and robust against geometric attacks.

A Method of Discriminative Features Extraction for Restricted Boltzmann Machines

The Restricted Boltzmann Machine (RBM) is a kind of stochastic neural network. It can be used as basic building blocks to form deep architectures. Since Hinton solved the problem of computational inefficiency by using a so called greedy layer-wise unsupervised pre-training algorithm, much more attention is focused on deep learning and achieved significant success in areas of speech recognition, object recognition, natural language processing, etc. In addition to initializing deep networks, RBMs can also be used to learn features from the raw data. In this paper, we proposed a method to learn much better discriminative features for RBMs based on using a novel objective function. We test our idea on MNIST handwritten digit dataset. In our experiments, the features learnt by RBM were further fed to a multinomial logistic regression and results show that our objective function could result in much higher accuracy ratio of classification.