A Tweakable Image Encryption Algorithm Using an Improved Logistic Chaotic Map

Herbadji, Djamel; Derouiche, Nadir; Belmeguenaï, Aïssa; Herbadji, Abderrahmane; Boumerdassi, Selma

doi:10.18280/ts.360505

Cited by 31 publications

(13 citation statements)

References 36 publications

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“…Step 2: Chaotic matrix S is converted into integer form to produce diffusion matrix D as in Equation (16).…”

Section: Diffusion Phasementioning

confidence: 99%

“…It has been found that the main problems of 1D chaotic maps are: (a) the chaotic range is relatively limited; (b) there is non-uniform distribution of data of the output chaotic sequences; (c) the proposed key is not sufficiently secure; (d) the attacks on random sequences are fast with a rather low computational cost. Consequently, some researchers have suggested an improved version of existing 1D chaotic maps in order to overcome 1D chaotic maps problems [14][15][16][17][18], while other researchers have suggested some novel 1D chaotic maps [19,20].…”

Section: Introductionmentioning

confidence: 99%

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Designing 1D Chaotic Maps for Fast Chaotic Image Encryption

et al. 2021

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Chaotic maps that can provide highly secure key sequences and ease of structure implementation are predominant requirements in image encryption systems. One Dimensional (1D) chaotic maps have the advantage of a simple structure and can be easily implemented by software and hardware. However, key sequences produced by 1D chaotic maps are not adequately secure. Therefore, to improve the 1D chaotic maps sequence security, we propose two chaotic maps: 1D Improved Logistic Map (1D-ILM) and 1D Improved Quadratic Map (1D-IQM). The proposed maps have shown higher efficiency than existing maps in terms of Lyapunov exponent, complexity, wider chaotic range, and higher sensitivity. Additionally, we present an efficient and fast encryption method based on 1D-ILM and 1D-IQM to enhance image encryption system performance. This paper also introduces a key expansion method to reduce the number of chaotic map iteration needs, thereby decreasing encryption time. The security analyses and experimental results are confirmed that 2D Correlation Coefficient (CC) Information Entropy (IE), Number of Pixels Change Rate (NPCR), Unified Average Changing Intensity (UACI), Mean Absolute Error (MAE), and decryption quality are able to meet the encryption security demands (CC = −0.00139, IE = 7.9990, NPCR = 99.6114%, UACI = 33.46952% and MAE = 85.3473). Furthermore, the proposed keyspace reaches 10240, and the encryption time is 0.025s for an image with a size of 256 × 256. The proposed system can yield efficacious security results compared to obtained results from other encryption systems.

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“…Step 2: Chaotic matrix S is converted into integer form to produce diffusion matrix D as in Equation (16).…”

Section: Diffusion Phasementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Designing 1D Chaotic Maps for Fast Chaotic Image Encryption

et al. 2021

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“…Logistics heat has always been a hot topic in the research of the logistics industry [11][12][13][14][15]. Lan and Zhong [16] carried out entropy analysis and classification of the data collected from online logistics heat maps, aiming to optimize the spatial pattern of logistics in economic development zones.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Regional Logistics Heat and Coupling Development between Regional Logistics and Economic Systems

Yin

Peng

2021

Discrete Dynamics in Nature and Society

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The research on logistics heat facilitates the understanding of the drivers of regional logistics development. However, many scholars ignore the difference between prediction methods in terms of attributes and focal points of data analysis during the selection of regional logistics heat prediction model. Regional logistics interacts with regional economy. However, the studies on the coupling development between the two systems fail to make a detailed analysis in the light of their actual situation. Therefore, the evaluation of the coordination degree is often biased. To solve the problem, this paper probes into the prediction of regional logistics heat and the coupling development between regional logistics and economic systems. Firstly, an index system was established to measure the level of coupling development between the two systems, and a grey relational analysis was performed on the indices, leading to the evaluation results on coordination degree. Next, a composite model of GM (1, 1) and backpropagation (BP) neural network was proposed, and the deviation interval of the composite predictions was predicted based on Markov chain prediction model. The proposed algorithm proved effective through experiments.

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“…In the recent years, researchers have developed many image encryption schemes based on different theories like: chaos [3][4][5][6][7][8], Deoxyribonucleic Acid (DNA) [9][10][11][12] and Substitution-Box (S-box) [13][14][15]. These schemes were designed to solve different problems.…”

Section: Introductionmentioning

confidence: 99%

Cryptanalysis of a Pixel Permutation Based Image Encryption Technique Using Chaotic Map

Mokhnache¹,

Ziet²

2020

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Recently, a new image encryption algorithm was proposed by Anwar and Meghana. This encryption scheme uses the Arnold's chaotic cat map to permute the image pixels. The resulting image is then confused with both a secret image provided as part of the secret key and a secret value selected randomly from the permuted image. Using a random image as part of the secret key, gives this algorithm an infinite key space which increases its efficiency against brute-force attacks. In order to help improving the security of modern image encryption schemes, this paper presents a cryptanalysis of the proposed algorithm using a combination of chosen-plaintext and brute-force attacks. First, the infinite key space that the secret image offers is broken using a chosen-plaintext attack. Then, the permutation phase is reversed through a series of chosen-plaintext attacks too. Finally, the secret value chosen randomly from the permuted image is easily brute-forced due to its reduced number of possible values. By applying the above method, it is possible to restore the plain version of any image that was encrypted using the former encryption algorithm. Thus, relying on this algorithm to encrypt real sensitive data is not secure.

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A Tweakable Image Encryption Algorithm Using an Improved Logistic Chaotic Map

Cited by 31 publications

References 36 publications

Designing 1D Chaotic Maps for Fast Chaotic Image Encryption

Designing 1D Chaotic Maps for Fast Chaotic Image Encryption

Prediction of Regional Logistics Heat and Coupling Development between Regional Logistics and Economic Systems

Cryptanalysis of a Pixel Permutation Based Image Encryption Technique Using Chaotic Map

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