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Go to Editorial ManagerIn 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.
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.
The paper presents a novel approach that merges the abilities of the biological environment with the concept of hierarchical trees to attack a specific stream cipher. The model being presented introduces a systematic method that targets a group of stream ciphers, such as the GCM family, these devices are composed of components that are suitable for the proposed method. A restricted set of binaries for the final key sequence is required to implement this technique as an input. The attacked algorithm comprises feedback shift registers, memories, delays, and so on. The stream ciphers are widely used in modern encryption to secure communication devices, so any attempt to analyze or attack it is of the utmost importance. The results of this method have been confirmed to lead to the destruction of the cipher’s security. Many novelties and contributions of the present work can be summarized as follows: firstly, the key generator’s components are attacked individually, disrupting the cohesion between them. This was not possible previously except in rare cases and under difficult conditions. Secondly, the method of verifying the correct initial values is unrelated to the generator’s operation. Thirdly, the technique applies biological concepts and processes to laboratory test tubes for genetic engineering, it can be said that the prepared model targets a broad class of stream key generators, rather than a single algorithm. The proposed technique requires a specific and deterministic number of final key sequence bits, which are easy to provide. The proposed technique creates a search E -tree in the style of hierarchical clusters, in which the first level containsE nodes. Then each successive level contains the square of E nodes of the number of nodes in the previous level, and the root is composed of the total solution space of the stream key generator and produces the nodes of each level from the intersection of the cluster contents in the test tubes for all clusters in the level above it. The contribution and novelty of the present work is cryptanalyzing and attacking shift register-based stream key generators involves fragmentation. The attacking principle entails disassembling generator components from registers and individually attacking them. DNA logic clustering aids in this process, as the strength of these generators relies on component cohesion. Because the components are cryptanalyzed individually, the time complexity of the attack is equal to O(C2N) , where N is the length of the largest component, and C is a constant.