A chaotic image encryption scheme owning temp-value feedback

This paper presents a novel efficient chaotic image encryption scheme, in which the temp-value feedback mechanism is introduced to the permutation and diffusion procedures. Firstly, a simple trick is played to map the plain-image pixels to the initial condition of the Logistic map. Then, a pseudorandom number sequence (PRNS) is obtained from iterating the map. The permutation procedure is carried out by a permutation sequence which is generated by comparing the PRNS and its sorted version. The diffusion procedure is composed of two reversely executed rounds. During each round, the current plain-image pixel and the last cipher-image pixel are used to produce the current cipher-image pixel with the help of the Logistic map and a pseudorandom number generated by the Chen system. To enhance the efficiency, only expanded XOR operation and modulo 256 addition are employed during diffusion. Experimental results show that the new scheme owns a large key space and can resist the differential attack. It is also efficient.Comment: 10 pages, 4 figure

Chaotic-Based Encryption Algorithm using Henon and Logistic Maps for Fingerprint Template Protection

Fingerprint is a reliable user authentication method as it is unique to individual users that makes it efficient for authenticating users. In a fingerprint authentication system, user fingerprint information is stored in databases in an image format known as a fingerprint template. Although fingerprint is reliable, the templates stored in the database are exposed to security threats either during the data transmission process over the network or in storage. Therefore, there is a need to protect the fingerprint template, especially in unsecured networks to maintain data privacy and confidentiality. Many past studies proposed fingerprint template protection (FTP) using chaotic-based encryption algorithms that are more suitable to secure images than conventional encryption such as DES, AES, and RSA. The chaotic-based encryption algorithms have been improved a lot in terms of their robustness. However, the robustness of the algorithm caused a trade-off to encryption speed where it remains an issue in FTP.  Hence, this study aims to improve the limitations found in the existing chaotic-based encryption algorithms for FTP by improving its encryption speed using Henon and Logistic map. A series of simulations were conducted using MATLAB to evaluate the performance of the proposed chaotic-based encryption algorithm for FTP through different analyses covering key sensitivity, histogram, correlations, differential, information entropy, and encryption/decryption speed. The performance proposed encryption algorithm was promising which could be a starting point for detailed analysis and implementation in real application domains

Joint block and stream cipher based on a modified skew tent map

Image encryption is very different from that of texts due to the bulk data capacity and the high redundancy of images. Thus, traditional methods are difficult to use for image encryption as their pseudo-random sequences have small space. Chaotic cryptography use chaos theory in specific systems working such as computing algorithms to accomplish dissimilar cryptographic tasks in a cryptosystem with a fast throughput. For higher security, encryption is the approach to guard information and prevent its leakage. In this paper, a hybrid encryption scheme that combines both stream and block ciphering algorithms is proposed in order to achieve the required level of security with the minimum encryption time. This scheme is based on an improved mathematical model to cover the defects in the previous discredited model proposed by Masuda. The proposed chaos-based cryptosystem uses the improved Skew Tent Map (STM) RQ-FSTM as a substitution layer. This map is based on a lookup table to overcome various problems, such as the fixed point, the key space restrictions, and the limitation of mapping between plain text and cipher text. It uses the same map as a generator to change the byte position to achieve the required confusion and diffusion effects. This modification improves the security level of the original STM. The robustness of the proposed cryptosystem is proven by the performance and the security analysis, as well as the high encryption speed. Depending on the results of the security analysis the proposed system has a better dynamic key space than previous ones using STM, a double encryption quality and a better security analysis than others in the literature with speed convenience to real-time applications

Chaotic-based encryption algorithm using henon and logistic maps for fingerprint template protection

Fingerprint is a reliable user authentication method as it is unique to individual users that makes it efficient for authenticating users. In a fingerprint authentication system, user fingerprint information is stored in databases in an image format known as a fingerprint template. Although fingerprint is reliable, the templates stored in the database are exposed to security threats either during the data transmission process over the network or in storage. Therefore, there is a need to protect the fingerprint template, especially in unsecured networks to maintain data privacy and confidentiality. Many past studies proposed fingerprint template protection (FTP) using chaotic-based encryption algorithms that are more suitable to secure images than conventional encryption such as DES, AES, and RSA. The chaotic-based encryption algorithms have been improved a lot in terms of their robustness. However, the robustness of the algorithm caused a trade-off to encryption speed where it remains an issue in FTP. Hence, this study aims to improve the limitations found in the existing chaotic-based encryption algorithms for FTP by improving its encryption speed using Henon and Logistic map. A series of simulations were conducted using MATLAB to evaluate the performance of the proposed chaotic-based encryption algorithm for FTP through different analyses covering key sensitivity, histogram, correlations, differential, information entropy, and encryption/decryption speed. The performance proposed encryption algorithm was promising which could be a starting point for detailed analysis and implementation in real application domains

DNA and Plaintext Dependent Chaotic Visual Selective Image Encryption

Visual selective image encryption can both improve the efficiency of the image encryption algorithm and reduce the frequency and severity of attacks against data. In this article, a new form of encryption is proposed based on keys derived from Deoxyribonucleic Acid (DNA) and plaintext image. The proposed scheme results in chaotic visual selective encryption of image data. In order to make and ensure that this new scheme is robust and secure against various kinds of attacks, the initial conditions of the chaotic maps utilized are generated from a random DNA sequence as well as plaintext image via an SHA-512 hash function. To increase the key space, three different single dimension chaotic maps are used. In the proposed scheme, these maps introduce diffusion in a plain image by selecting a block that have greater correlation and then it is bitwise XORed with the random matrix. The other two chaotic maps break the correlation among adjacent pixels via confusion (row and column shuffling). Once the ciphertext image has been divided into the respective units of Most Significant Bits (MSBs) and Least Significant Bit (LSBs), the host image is passed through lifting wavelet transformation, which replaces the low-frequency blocks of the host image (i.e., HL and HH) with the aforementioned MSBs and LSBs of ciphertext. This produces a final visual selective encrypted image and all security measures proves the robustness of the proposed scheme

Entropy in Image Analysis III

Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future