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Go to Editorial ManagerThis paper presents a simple method for the design of Chaotic Linear Feedback Shift Register (CLFSR) system. The proposed method is based on a combination of two known systems. The first is called Linear Feedback Shift Register (LFSR) system, and the other is called Chaotic Map system. The main principle of the proposed system is that, the output of the LFSR is modified by exclusive-or (XOR) it with the stream bit that is generated by using the chaotic map system to eliminate the linearity and the repeating in the output of the LFSR system. The proposed system is built under Matlab environment and the quality of sequence generation tested by using standard tests which shows that the proposed system is a good random number generator that overcome the linearity and repeating disadvantages.
In this work, a new image encryption method using a combined multilevel permutation with stream cipher is proposed. In the permutation algorithm, image is divided into blocks in each level and its blocks are rearranged by using pseudorandom permutation method. A new non linear stream cipher algorithm is also proposed that is based on combining several keys generated by Linear Feedback Shift Register (LFSR). The results shown that the proposed algorithm has a high security feature and it is efficient for image encryption. Practical tests proved that the proposed encryption algorithm is robust, provides high level of security and gives perfect reconstruction of the decrypted image.
In nowadays world of rapid evolution of exchanging digital data, data protection is required to protect data from the unauthorized parities. With the widely use of digital images of diverse fields, it is important to conserve the confidentiality of image’s data form any without authorization access. In this paper the problem of secret key exchanging with the communicated parities had been solved by using a random number generator which based on Linear Feedback Shift Register (LFSR). The encryption/decryption is based on Advance Encryption Standard (AES) with the random key generator. Also, in this paper, both grayscale and colored RGB images have been encrypted/decrypted. The functionality of proposed system of this paper, is concerned with three features: First feature, is dealing with the obstetrics of truly random and secure encryption key while the second one deals with encrypting the plain or secret image using AES algorithm and the third concern is the extraction the original image by decrypting the encrypted or cipher one. “Mean Square Error (MSE)”, “Peak Signal to Noise Ratio (PSNR)”, “Normalized Correlation (NK)”, and “Normalized Absolute Error (NAE)” are measured for both (original-encrypted) images and (original-decrypted) image in order to study and analyze the performance of the proposed system according to image quality features.
Nonlinear stream ciphers have become a viable alternative to traditional cryptosystems in response to the growing need for secure communication. These ciphers generate a keystream via feedback mechanisms and nonlinear functions, which are then utilized for encryption. Geffe generator system is one of the most keystream generators. Also, these systems have many benefits, like being fast, flexible, and able to create unpredictable and non-repeating keystreams, these systems are susceptible to cryptanalysis attacks, which have the potential to compromise their security. This paper presents the first study of applying chicken swarm optimization (CSO) algorithm in the field of cryptanalysis based on cipher only attack. The standard CSO algorithm and an adaptive multi points CSO (AMPCSO) algorithm are proposed to cryptanalysis nonlinear stream cipher based on Geffe keystream generator. Firstly, the traditional CSO is used to reveal the secret initial values of the Geffe generator. Secondly, an adaptive multi points chicken swarm optimization (AMPCSO) has been proposed to enhance the traditional CSO algorithm to attack Geffe generator systems. The AMPCSO is a new idea to advance the CSO search abilities and improve the foraging behavior of hens and chicks by allowing hens to be influenced by other individuals within the same or different groups and affected by the best individual in the population and enable chicks to learn from four reference points rather than learn from their respective mothers only. Lastly, a new criterion is used to estimate the value of fitness by utilizing a multi-objective fitness function (MOFF), which is grounded on Pareto dominance. The experimental results showed that the CSO and AMPCSO are very effective tools in terms of accuracy, information required, and CPU times when applied to the analysis of nonlinear stream cipher. The AMPCSO required a few characters from ciphertext to attack systems with total LFSRs length up to 59 bits with an appropriate CPU time.