An efficient image encryption scheme using elementary cellular automata with novel permutation box

Evolution-in-Materio (EIM) is a method of using artificial evolution to exploit physical properties of materials for computation. It has previously been successfully used to evolve a multitude of different computational devices implemented in physical materials. One of the main problems has been the stability of solutions due to physical changes in the substrate materials, e.g. topological or electrical, leading to devices sensitive to the evolutionary history, i.e. instability. This paper presents stable linearly and non-linearly separable logic gates, and elementary cellular automata (CA) transition functions, successfully evolved in single-walled carbon nanotube (SWCNT) and polymer composite materials. The results herein show the feasibility of building stand-alone in-materio devices and outline a novel computational abstraction for EIM based on CA. This work is done within the European Project NASCENCE.

To evaluate the quality of microlithography result, massive aerial images are often generated for careful inspection using applications such as OPC LCC (Lithography Compaliance Check). The number of the pixels used in a 2D aerial image is in the order of 0(n * n), where n is the image resolution, which means the runtime scales in a n 2 fashion. However, most of the quality indexes such as CDs or EPE (Edge Placement Error) can be readily observed using contours only and the number of pixels in a specific contour is around O(n) in general. Therefore, there is a huge waste (at least O(n)) of both computation time and memory in most microlithography aerial image simulation tools. The question is: how to compute an image contour without explicitly generate images?. In this paper, we show that it is indeed feasible to know the image contour with an explicit image formation. The concept is to represent the image in an implicit way. In our algorithm, we utilize hierarchical region-wise function such as 2D polynomials to fit the aerial image kernels instead of using a bitmap type fit. Therefore, any LUT (Look-up-table) operation can be transformed into a polynomial look up and mathematical operations. Since there are only additive and subtractive operations during aerial image generation, we only need to apply same operations to the polynomial coefficients. Once the LUT operation is done, we have analytical forms of the light intensity in each region. To know the contour at each region, we only need to solve a local 2D polynomial equation. With these simple forms, the equation solution can be performed with great efficiency. Furthermore, due to the hierarchical structure, we can reduce the search time from O(m*m) to O(m logm), where m is the number of regions. Further speed up is achieved this way. Finally, our algorithm also does not suffer from increased feature count caused by the feature size reduction between process nodes because once the regional polynomial representation is complete, no future LUT search is necessary. Therefore, the runtime of our algorithm is significantly faster than the traditional image LUT method. The initial experiment demonstrates over hundreds of times speed up over the traditional LUT methods.

Recently, transformation of information is an emerging area of interest because of efficient Internet technology and faster communication medium. Nowadays, huge numbers of data transferred over many transferring mediums, out of which image is one of them. To maintain confidentiality and provide ownership of the data, we need to do any cryptographic technique like encryption. In this paper, we proposed a new cryptography technique for image encryption which is a combination of two different techniques for image encryption to increase the security of the data. The two different techniques are Zaslavskii map and Arnold’s cat map. Both combinedly used for encryption as well as decryption. In this work, we first encrypt the image using Zaslavskii method, and then again, that encrypted image re-encrypted using Arnold’s cat map to re-encrypt that, to get the required image using two times encryption. Then, in the reverse process, the final encrypted image undergoes first decryption using Arnold’s cat map, and that decrypted image further undergoes Zaslavskii decryption to get back the final derived image which should be like the original image. This proposed technique gives users more key values for better security and unpredictability, which shows good entropy value and good correlation value. The efficiency of image encryption techniques is verified by number of pixels change rate (NPCR) and unified average chaning intensity (UACI) which is used for any small change in pixels, along with entropy and correlation coefficient values.

In recent years, encryption technology has been developed quickly and many image encryption methods have been put forward. Chaos based image encryption technique is a new encryption technique for images. It utilizes chaos random sequence to encrypt image, which is an efficient way to deal with the intractable problem of fast and highly secure image encryption. However, the Chaos based image encryption technique has some deficiencies, such as the limited accuracy problem. This paper researches on the chaotic encryption, DES encryption and a combination of image encryption algorithm, and simulate these algorithms, through analysis of the algorithm to find the gaps. And on this basis, the algorithm has been improved. The new encryption scheme realizes the digital image encryption through the chaos and improving DES. Firstly, new encryption scheme uses the Logistic chaos sequencer to make the pseudo-random sequence, carries on the RGB with this sequence to the image chaotically, then makes double time encryptions with improvement DES, displays they respective merit. Theoretical analysis and the simulation indicate that this plan has the high starting value sensitivity, and enjoys high security and the encryption speed. In addition it also keeps the neighboring RGB relevance close to zero. The algorithm can be used in the actual image encryption.

This paper proposes an image encryption technique for smart phones devices to encrypt images and then upload on the cloud. The process of retrieving and decrypting images will be under full control by the user. Also, if the user wants to retrieve an image, he can retrieve it completely, but not as he needed. Our research can solve two main issues in current mobile applications which will protect photo that will be decrypt by the user only, and will help the user to recover the photo needed. An encryption mechanism based on hybrid between elementary cellular automata (ECA) and RC4 algorithms are used to encrypt images on the smart android mobiles. Experimental results on the application showed that our proposed encryption technique used for image encryption has a good quality en cryption with secure requirements.

This paper explores the concept of isomorphism in cellular automata (CAs), focusing on identifying and understanding isomorphic relationships between distinct CAs. A cellular automaton (CA) is said to be isomorphic to another CA if the configuration transition diagrams of the two CAs are identical. To illustrate how isomorphism entails the preservation of structural properties while allowing for variations in state representations, we exhaustively explore the isomorphic reversible rules in the first degree CAs (FDCAs), that is, the simple three-neighborhood CAs represented by eight parameters. The experimental study includes reversible FDCAs for states two to 10 with cell lengths of four to seven under the null boundary condition and states two to seven with cell lengths of four to seven under the periodic boundary condition. Given a CA, we also provide two synthesis methods for identifying the set of CAs that are isomorphic to it. The first method operates by permuting the states of a group of CA cell locations, whereas the second method involves exchanging cells at various points. We demonstrate that, depending on the range of exchanged cell positions, the isomorphic CAs produced in this way may have a bigger neighborhood than the input CA. Finally, we provide an exhaustive classification of the elementary CAs (ECAs) using the first synthesis method and compare it with existing results.

Cryptography is a technique used today hiding any confidential information from the attack of an intruder. Today data communication mainly depends upon digital data communication, where prior requirement is data security, so that data should reach to the intended user. The protection of multimedia data, sensitive information like credit cards, banking transactions and social security numbers is becoming very important. The protection of these confidential data from unauthorized access can be done with many encryption techniques. So for providing data security many cryptography techniques are employed, such as symmetric and asymmetric techniques. In this review paper different asymmetric cryptography techniques, such as RSA (Rivest Shamir and Adleman), Diffie-Hellman, DSA (Digital Signature Algorithm), ECC (Elliptic curve cryptography) are analyzed. Also in this paper, a survey on existing work which uses different techniques for image encryption is done and a general introduction about cryptography is also given. This study extends the performance parameters used in encryption processes and analyzing on their security issues.

A color image encryption scheme based on 1D cubic map

We propose a method of constructing differential equations directly from cellular automata. Any elementary cellular automata (ECAs) introduced by Wolfram can be transformed into a partial differential equation (PDE) which preserves the time evolution patterns of the ECAs. In particular, some PDEs constructed by the method reproduce complex fractal and self-organizing patterns found in their corresponding ECAs. It is expected that the method can be extended for general cellular automata with more complex rules and/or in higher dimensions.

This paper proposes an unique image encryption scheme in the hybrid domain based on Logistic Map, Reversible Integer Wavelet Transform, and Elementary Cellular Automata (CA). In the proposed work, position permutation is done using Logistic Map equation in the spatial domain and pixel value transformation is done using CA rule and randomly generated matrix created using Logistic map equation in the Transfer Domain with the help of Reversible Integer Wavelet Transform. This paper handouts a pristine application of Logistic map functions and CA in the transfer domain and in spatial domain. Analysis shows that the relationship among the transfer domain coefficients is greatly reduced and the randomness metric is equal to 7.999 much closer to the ideal value of 8.

Cellular Automata (CA) have a long history being employed as pseudo-random number generators (PRNG), especially for cryptographic applications such as keystream generation in stream ciphers. Initially starting from the study of rule 30 of elementary CA, multiple rules where the objects of investigation and were shown to be able to pass most of the rigorous statistical tests used to assess the quality of PRNG. In all cases, the CA employed where of the classical, synchronous kind. This assumes a global clock regulating all CA updates which can be a weakness if an attacker is able to tamper it. Here we study how much asynchrony is necessary to make a CA-based PRNG ineffective. We have found that elementary CA are subdivided into three class: (1) there is a “state transition” where, after a certain level of asynchrony, the CA loses the ability to generate strong random sequences, (2) the randomness of the sequences increases with a limited level of asynchrony, or (3) CA normally unable to be used as PRNG exhibit a much stronger ability to generate random sequences when asynchrony is introduced.

In the last decade, the communication of images through the internet has increased. Due to the growing demands for data transfer through images, protection of data and safe communication is very important. For this purpose, many encryption techniques have been designed and developed. New and secured encryption schemes based on chaos theory have introduced methods for secure as well as fast communication. A modified image encryption process is proposed in this work with chaotic maps and orthogonal matrix in Hill cipher. Image encryption involves three phases. In the first phase, a chaotic Henon map is used for permuting the digital image. In the second phase, a Hill cipher is used whose encryption key is generated by an orthogonal matrix which further is produced from the equation of the plane. In the third phase, a sequence is generated by a chaotic tent map which is later XORed. Chaotic maps play an important role in the encryption process. To deal with the issues of fast and highly secured image processing, the prominent properties of non-periodical movement and non-convergence of chaotic theory play an important role. The proposed scheme is resistant to different attacks on the cipher image. Different tests have been applied to evaluate the proposed technique. The results of the tests such as key space analysis, key sensitivity analysis, and information entropy, histogram correlation of the adjacent pixels, number of pixel change rate (NPCR), peak signal to noise ratio (PSNR), and unified average changing intensity (UCAI) showed that our proposed scheme is an efficient encryption technique. The proposed approach is also compared with some state-of-the-art image encryption techniques. In the view of statistical analysis, we claim that our proposed encryption algorithm is secured.

Optimized Chaotic encrypted image based on continuous raster scan method

Random Boolean networks (RBN) and Cellular Automata (CA) operate in a very similar way. They update their state with simple deterministic functions called Boolean function or Transition Table (TT), both being essentially the same mechanism under different names. This paper applies a concept most known from CA called Minimum Equivalence (ME). ME is applied to RBN and shows how to calculate the number of unique computations for a given number of neighbours. Crucially, it is shown how RBN rules are even more equivalent than in CA, how the set can be reduced into even fewer unique rules, and how the concept becomes more relevant with larger neighbourhoods. For example, switching transformation alone reduces the number of unique rules in RBN with 4 neighbours from 65 536 to only 3 984 (6.1%) rules. Additionally, this paper examines the ME and transformations in substrates beyond Elementary CA (ECA), such as CA with additional spatial dimensions and number of states.

To enhance image privacy protection and reduce storage space, this paper proposes an image compression and encryption algorithm that combines compressed sensing, Hachimoji DNA coding, and a 7D hyperchaotic system. The algorithm processes the high-frequency and low-frequency parts after the wavelet transform separately. Sparse high-frequency information is compressed by low-compression measurement. The low-frequency part uses block-compressed sensing, and only a small amount of data is needed to reconstruct a high-quality image. In addition, the measurement matrix is constructed by chaotic sequence, which reduces the demand for memory and transmission bandwidth. To protect compressed data, this paper also presents an image encryption algorithm based on Hachimoji DNA dynamic coding and Joseph dynamic traversal. The algorithm first uses Joseph traversal to disturb the bit position of each pixel dynamically and then implements Hachimoji DNA dynamic coding. At the same time, a new Joseph bidirectional dynamic scrambling-diffusion algorithm is proposed, which gives the encrypted image a uniform grayscale histogram, high information entropy, and sensitivity to resist various attacks effectively.