Cryptanalysis of an Image Encryption Algorithm Based on Random Walk and Hyperchaotic Systems

Fan, Hui; Lü, Heng; Zhang, Chenjiu; Li, Ming; Liu, Yanfang

doi:10.3390/e24010040

Cited by 10 publications

(6 citation statements)

References 32 publications

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“…Te higher the NPCR value, the more resilient the encryption against diferential attacks [52]. Te NPCR ideal value is 99.6094% [53]. NPCR is found by [54][55][56].…”

Section: Number Of Pixels Changementioning

confidence: 99%

An Integration of New Digital Image Scrambling Technique on PCA-Based Face Recognition System

Abusham

Ibrahim

Zia

et al. 2022

Scientific Programming

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Systems using biometric authentication offer greater security than traditional textual and graphical password-based systems for granting access to information systems. Although biometric-based authentication has its benefits, it can be vulnerable to spoofing attacks. Those vulnerabilities are inherent to any biometric-based subsystem, including face recognition systems. The problem of spoofing attacks on face recognition systems is addressed here by integrating a newly developed image encryption model onto the principal component pipeline. A new model of image encryption is based on a cellular automaton and Gray Code. By encrypting the entire ORL faces dataset, the image encryption model is integrated into the face recognition system’s authentication pipeline. In order for the system to grant authenticity, input face images must be encrypted with the correct key before being classified, since the entire feature database is encrypted with the same key. The face recognition model correctly identified test encrypted faces from an encrypted features database with 92.5% accuracy. A sample of randomly chosen samples from the ORL dataset was used to test the encryption performance. Results showed that encryption and the original ORL faces have different histograms and weak correlations. On the tested encrypted ORL face images, NPCR values exceeded 99%, MAE minimum scores were over (>40), and GDD values exceeded (0.92). Key space is determined by u 2 s i z e A 0 where A0 represents the original scrambling lattice size, and u is determined by the variables on the encryption key. In addition, a NPCR test was performed between images encrypted with slightly different keys to test key sensitivity. The values of the NPCR were all above 96% in all cases.

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“…Te higher the NPCR value, the more resilient the encryption against diferential attacks [52]. Te NPCR ideal value is 99.6094% [53]. NPCR is found by [54][55][56].…”

Section: Number Of Pixels Changementioning

confidence: 99%

An Integration of New Digital Image Scrambling Technique on PCA-Based Face Recognition System

Abusham

Ibrahim

Zia

et al. 2022

Scientific Programming

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“…In the process of analyzing the security of the encryption algorithm, attackers try various methods to crack the algorithm and gradually develop some classic cryptanalysis methods. In [ 34 ], an encryption scheme based on a random walk matrix and a hyperchaotic system was cracked by the chosen plaintext attack method, and relevant suggestions were given for its security loopholes to improve the anti-attack capability; in [ 35 ], an image encryption algorithm combining DNA coding and a spatiotemporal chaotic system was analyzed; its equivalent key can be obtained by the chosen ciphertext attack method according to its defects, and it recovered the plaintext image; in [ 36 ], when a chaotic image encryption algorithm based on information entropy was cryptanalyzed for the effectiveness of quantifiable security measures, the differential attack method can be used to recover the equivalent key of each basic operation of the encryption algorithm.…”

Section: Introductionmentioning

confidence: 99%

Cryptanalysis of an Image Encryption Algorithm Based on Two-Dimensional Hyperchaotic Map

Jiang

Wang

2023

Entropy

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This paper analyzes the security of an image encryption algorithm based on a two-dimensional hyperchaotic map. This encryption algorithm generated chaotic sequences through a combination of two one-dimensional chaotic maps and used them as the permutation and diffusion key. Then, the image was encrypted by using the structure of row–column permutation, forward-diffusion, and backward-diffusion. The proposer claimed that the above algorithm was secure. However, it was found through cryptanalysis that the algorithm cannot withstand the chosen plaintext attack. Although the forward-diffusion and backward-diffusion of the original algorithm use two different diffusion keys and there is a ciphertext feedback mechanism, the analysis of the diffusion by iterative optimization showed that it can be equivalent to global diffusion. In addition, the generation of chaotic sequences in the encryption process is independent of the plaintext image, so the equivalent diffusion and permutation key stream can be obtained by adjusting the individual pixel values of the chosen plaintexts. Aiming at the security loopholes in the encryption algorithm, the theoretical and experimental results are presented to support the efficiency of the proposed attack and suggestions for improvement are given. Finally, compared with the performance analysis of the existing cracking algorithm, our cryptanalysis greatly improved the cracking efficiency without increasing the complexity of the data.

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“…This makes the system significantly harder to crack, as breaking even a single key will only allow the attacker access to less than four bytes of data. This is critical for high-security systems, as methods have been introduced that can break a single-seed Lorenz system using synchronization methods [3], machine learning detection of initial conditions [4], or various other crypt-analysis techniques such as plaintext attacks [5][6][7]. With our implementation of frequently refreshed keys, our system is immune to plaintext and side-channel attacks that the predecessors fell victim to.…”

Section: Introductionmentioning

confidence: 99%

Integrating Lorenz Hyperchaotic Encryption with Ring Oscillator Physically Unclonable Functions (RO-PUFs) for High-Throughput Internet of Things (IoT) Applications

Magyari,

Chen

2023

Electronics

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With the combined call for increased network throughput and security comes the need for high-bandwidth, unconditionally secure systems. Through the combination of true random number generators (TRNGs) for unique seed values, and four-dimensional Lorenz hyperchaotic systems implemented on a Stratix 10 Intel FPGA, we are able to implement 60 MB/s encryption/decryption schemes with 0% data loss on an unconditionally secure system with the NIST standard using less than 400 mW. Further, the TRNG implementation allows for unique encryption outputs for similar images while still enabling proper decryption. Histogram and adjacent pixel analysis on sample images demonstrate that without the key, it is not possible to extract the plain text from the encrypted image. This encryption scheme was implemented via PCIe for testing and analysis.

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Cryptanalysis of an Image Encryption Algorithm Based on Random Walk and Hyperchaotic Systems

Cited by 10 publications

References 32 publications

An Integration of New Digital Image Scrambling Technique on PCA-Based Face Recognition System

An Integration of New Digital Image Scrambling Technique on PCA-Based Face Recognition System

Cryptanalysis of an Image Encryption Algorithm Based on Two-Dimensional Hyperchaotic Map

Integrating Lorenz Hyperchaotic Encryption with Ring Oscillator Physically Unclonable Functions (RO-PUFs) for High-Throughput Internet of Things (IoT) Applications

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