New method for fingerprint images encryption using DNA sequence and chaotic tent map

Nezhad, Shadi Yoosefian Dezfuli; Safdarian, Naser; Zadeh, Seyed Ali Hoseini

doi:10.1016/j.ijleo.2020.165661

Cited by 45 publications

(10 citation statements)

References 35 publications

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“…NPCR, UACI, correlation coefcient, and entropy values of the proposed method are compared with previous studies in Table 5. Te proposed system is similar to [30,46] and gave better results than [48] for NPCR and UACI values. According to the average correlation coefcient values, the proposed system is slightly behind [45,46], but gives better results than [48].…”

Section: Discussionmentioning

confidence: 81%

“…According to the average correlation coefcient values, the proposed system is slightly behind [45,46], but gives better results than [48]. According to the entropy value, the proposed system achieved the best results in [30,46,[48][49][50]. In totality, the quadratic megastable system-based Complexity encryption emerges as a robust and efective method securing fngerprint images.…”

Section: Discussionmentioning

confidence: 93%

“…In equation (10), N represents the number of symbols, x i is the pixel value and p(x i ) represents the probability that x i will appear in the data stack. Te N value for the 8 bit depth of the grayscale fngerprint image used in the study is 8 [16,20,26,27,30].…”

Section: Entropy Analysismentioning

confidence: 99%

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Dynamical Analysis of a Quadratic Megastable Chaotic Oscillator and Its Application in Biometric Fingerprint Image Encryption

Subramanian,

Çiçek,

Akgul

et al. 2024

Complexity

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This investigation centers on megastable systems, distinguished by their countable infinite attractors, with a particular emphasis on the Quadratic Megastable Oscillator (QMO). Unlike traditional megastable oscillators reliant on external excitation, our proposed QMO operates autonomously, contributing to its distinctiveness. Through a comprehensive exploration of the QMO, we elucidate various dynamical behaviors, enriching the understanding of its complex system dynamics. In contrast to conventional megastable oscillators, the QMO yields nested types of multiple attractors for diverse initial conditions, elegantly depicted in phase portraits. To gauge the sustainability of chaotic oscillation, we employ influential parameter bifurcation plots, providing a nuanced insight into the system’s dynamical evolution. The complexity of the proposed system is further underscored by its intricate basins of attraction, accommodating an infinite number of coexisting attractors. Exploring trajectory dynamics, we observe that certain initial conditions lead trajectories to distant destinations, evading the influence of local attractors. This behavior underscores the uniqueness of the QMO and highlights its potential applications in scenarios requiring nonlocalized attractor behaviors. Taking a practical turn, the QMO is applied to biometric fingerprint image encryption, demonstrating its efficacy in real-world applications. Rigorous statistical analyses and vulnerability assessments confirm the success of the QMO in providing secure encryption within chaotic system-based frameworks. This research contributes not only to the theoretical understanding of megastable systems but also establishes the QMO as a valuable tool in encryption applications, emphasizing its robustness and versatility in complex dynamical scenarios.

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Section: Discussionmentioning

confidence: 81%

Section: Discussionmentioning

confidence: 93%

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Dynamical Analysis of a Quadratic Megastable Chaotic Oscillator and Its Application in Biometric Fingerprint Image Encryption

Subramanian,

Çiçek,

Akgul

et al. 2024

Complexity

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“…In Ref. [ 28 ], a fusion technique is proposed by implementing the Tent Chaotic Mapping (TCM) and DNA Sequence (DNA-S) models. At first, the initial and TCM images are put under the encryption process distinctly by implementing the DNA-S model.…”

Section: Related Workmentioning

confidence: 99%

Chaotic image encryption algorithm with improved bonobo optimizer and DNA coding for enhanced security

Almasoud,

Alabduallah,

Alqahtani

et al. 2024

Heliyon

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“…Information Entropy: It is a statistical measure of randomness. It is calculated using Equation ( 11) [22]:…”

Section: ) Computational and Time Complexity Analysismentioning

confidence: 99%

Gray-Scale Image Encryption Using DNA Operations

et al. 2022

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Unsecured networks have recently become widely used for the transmission of confidential images. Consequently, cryptography is crucial for ensuring data confidentiality. Developing a key that is resistant to statistical and differential attacks has always been a challenging objective. In this paper, a novel model is proposed to boost image encryption while maintaining key strength. The proposed model adapts MD5 and SHA-256 hash functions to produce a key. It generates four matrices, X, Y, Z, and W, by using a memristor hyperchaotic system. Arnold's transform was applied to the original image once the key was created. The images were then scrambled using five chaotic maps. The image is then DNA-encoded, diffused using three matrices, and finally DNA-decoded. The proposed model was assessed using twelve performance measures on nine popular images. Compared to previous studies, the results of the proposed model indicate a promising improvement in performance. It achieves a better performance by expanding the key space and increasing its sensitivity.

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New method for fingerprint images encryption using DNA sequence and chaotic tent map

Cited by 45 publications

References 35 publications

Dynamical Analysis of a Quadratic Megastable Chaotic Oscillator and Its Application in Biometric Fingerprint Image Encryption

Dynamical Analysis of a Quadratic Megastable Chaotic Oscillator and Its Application in Biometric Fingerprint Image Encryption

Chaotic image encryption algorithm with improved bonobo optimizer and DNA coding for enhanced security

Gray-Scale Image Encryption Using DNA Operations

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