scholarly journals Image encryption based on elliptic curve cryptosystem

2021 ◽  
Vol 11 (2) ◽  
pp. 1293
Author(s):  
Zahraa Kadhim Obaid ◽  
Najlae Falah Hameed Al Saffar
Keyword(s):  
Elliptic Curve ◽  
Image Encryption ◽  
Signal To Noise Ratio ◽  
Inverse Matrix ◽  
Elliptic Curve Cryptosystem ◽  
Secret Key ◽  
First Case ◽  
The Matrix ◽  
Hilbert Matrix ◽  
Generating Matrix

Image encryption based on elliptic curve cryptosystem and reducing its complexity is still being actively researched. Generating matrix for encryption algorithm secret key together with Hilbert matrix will be involved in this study. For a first case we will need not to compute the inverse matrix for the decryption processing cause the matrix that be generated in encryption step was self invertible matrix. While for the second case, computing the inverse matrix will be required. Peak signal to noise ratio (PSNR), and unified average changing intensity (UACI) will be used to assess which case is more efficiency to encryption the grayscale image.

scholarly journals Image Encryption Technology Based on Fractional Two-Dimensional Triangle Function Combination Discrete Chaotic Map Coupled with Menezes-Vanstone Elliptic Curve Cryptosystem

2018 ◽  
Vol 2018 ◽  
pp. 1-24 ◽  
Author(s):  
Zeyu Liu ◽  
Tiecheng Xia ◽  
Jinbo Wang
Keyword(s):  
Elliptic Curve ◽  
Image Encryption ◽  
Chaotic Map ◽  
Phase Portraits ◽  
Largest Lyapunov Exponent ◽  
Elliptic Curve Cryptosystem ◽  
Two Dimensional ◽  
Triangle Function ◽  
Function Combination ◽  
Secret Keys

A new fractional two-dimensional triangle function combination discrete chaotic map (2D-TFCDM) with the discrete fractional difference is proposed. We observe the bifurcation behaviors and draw the bifurcation diagrams, the largest Lyapunov exponent plot, and the phase portraits of the proposed map, respectively. On the application side, we apply the proposed discrete fractional map into image encryption with the secret keys ciphered by Menezes-Vanstone Elliptic Curve Cryptosystem (MVECC). Finally, the image encryption algorithm is analysed in four main aspects that indicate the proposed algorithm is better than others.

A Novel Public Key Image Cryptosystem Based on Elliptic Curve and Arnold Cat Map

2014 ◽  
Vol 989-994 ◽  
pp. 4183-4186
Author(s):  
Ling Jiao Chen ◽  
Ao Dong Shen
Keyword(s):  
Elliptic Curve ◽  
Image Encryption ◽  
Public Key ◽  
Elliptic Curve Cryptosystem ◽  
The Novel ◽  
Arnold Cat Map ◽  
High Security ◽  
Secret Keys ◽  
Image Cryptosystem

For decades, symmetric cryptosystems, such as chaos-based ones, are designed for image encryption. In this paper, a novel public key scheme for image encryption is presented. Based on the improved elliptic curve cryptosystem and Arnold cat map, the novel scheme can offer high security while avoid exchange and distribution of secret keys. The experiments illustrate that the presented scheme is computationally less complex than the traditional asymmetric cryptosystems and suitable for large image encryption.

scholarly journals Selective Image Encryption Based on DCT, Hybrid Shift Coding and Randomly Generated Secret Key

2020 ◽  
pp. 920-935
Author(s):  
Loay E. George ◽  
Enas Kh. Hassan ◽  
Sajaa G. Mohammed ◽  
Faisel G. Mohammed
Keyword(s):  
Image Encryption ◽  
Signal To Noise Ratio ◽  
Color Space ◽  
Image Data ◽  
Differential Pulse ◽  
Compression Algorithm ◽  
Secret Key ◽  
Encryption Decryption ◽  
Highly Correlated ◽  
Quantization Parameters

Most of today’s techniques encrypt all of the image data, which consumes a tremendous amount of time and computational payload. This work introduces a selective image encryption technique that encrypts predetermined bulks of the original image data in order to reduce the encryption/decryption time and thecomputational complexity of processing the huge image data. This technique is applying a compression algorithm based on Discrete Cosine Transform (DCT). Two approaches are implemented based on color space conversion as a preprocessing for the compression phases YCbCr and RGB, where the resultant compressed sequence is selectively encrypted using randomly generated combined secret key.The results showed a significant reduction in image quality degradation when applying the system based on YCbCr over RGB, where the compression ratio was raised in some of the tested images to 50% for the same Peak Signal to Noise Ratio (PSNR). The usage of 1-D DCT reduced the transform time by 47:1 times comparedto the same transform using 2-D DCT. The values of the adaptive scalar quantization parameters were reduced to the half for the luminance (Y band) to preserve the visual quality, while the chrominance (Cb and Cr bands) were quantized by the predetermined quantization parameters. In the hybrid encoder horizontal zigzag,block scanning was applied to scan the image. The Detailed Coefficient (DC) coefficients are highly correlated in this arrangement- where DC are losslessly compressed by Differential Pulse Coding Modulation (DPCM) and theAccumulative Coefficients (AC) are compressed using Run Length Encoding (RLE). As a consequence, for the compression algorithm, the compression gain obtained was up to 95%. Three arrays are resulted from each band (DC coefficients, AC values, and AC runs), where the cipher is applied to some or all of those bulksselectively. This reduces the encryption decryption time significantly, where encrypting the DC coefficients provided the second best randomness and the least encryption/decryption time recorded (3 10-3 sec.) for the entire image. Although the compression algorithm consumes time but it is more efficient than the savedencryption time. 

scholarly journals Dynamic fractional chaotic biometric isomorphic elliptic curve for partial image encryption

2021 ◽  
pp. 18-18
Author(s):  
Ahmed Kamal ◽  
Esam Hagras ◽  
H.A. El-Kamchochi
Keyword(s):  
Elliptic Curve ◽  
Image Encryption ◽  
High Speed ◽  
Chaotic Behavior ◽  
Key Exchange ◽  
Discrete Wavelet ◽  
Security Level ◽  
Differential Analysis ◽  
Digital Identity ◽  
Secret Key

In this paper, a Modular Fractional Chaotic Sine Map (MFC-SM) has been introduced to achieve high Lyapunov exponent values and completely chaotic behavior of the bifurcation diagram for high level security. The proposed MFC-SM is compared with the conventional non MFC-SM and it has an excellent chaotic analysis. In addition, the randomness test results indicate that the proposed MFC-SM shows better performance and satisfy all randomness tests. Due to the excellent chaotic properties and good randomization results for the proposed MFC-SM, it is used to be cooperated with the biometric digital identity to achieve dynamic chaotic biometric digital identity. Also, for real time image encryption, both Discrete Wavelet Transform (DWT) partial image encryption and Isomorphic Elliptic Curve (IEC) key exchange are used. In addition, the biometric digital identity is extracted from the user fingerprint image as fingerprint minutia data incorporated with the proposed MFC-SM and hence, a new Dynamic Fractional Chaotic Biometric Digital Identity IEC (DFC-BID-IEC) has been introduced. Dynamic Fractional Chaotic Key Generator (DFC-KG) is used to control the key schedule for all encryption and decryption processing. The encryption process consists of the confusion and diffusion steps. In the confusion step, the 2D Arnold Cat Map (ACM) is used with secret parameters taken from DFC-KG. Also, the diffusion step is based on the dynamic chaotic self-invertible secret key matrix which can be generated from the proposed MFC-SM. The IEC key exchange secret parameters are generated based on Elliptic Curve Diffie-Hellman (ECDH) key exchange and the isomorphism parametre. Statistical analysis, differential analysis and key sensitivity tests are performed to estimate the security strengths of the proposed DFC-BID-IEC system. The experimental results show that the proposed algorithm is robust against common signal processing attacks and provides a high security level and high speed for image encryption application.

Adaptive identification methods of nonlinear random electrical signal

2020 ◽  
Vol 64 (1-4) ◽  
pp. 431-438
Author(s):  
Jian Liu ◽  
Lihui Wang ◽  
Zhengqi Tian
Keyword(s):  
Wavelet Transform ◽  
Electric Vehicle ◽  
Signal To Noise Ratio ◽  
Sudden Change ◽  
Electrical Signal ◽  
Signal Recognition ◽  
State Variable ◽  
Signal Characteristics ◽  
The Matrix ◽  
Kalman Filter Algorithm

The nonlinearity of the electric vehicle DC charging equipment and the complexity of the charging environment lead to the complex and changeable DC charging signal of the electric vehicle. It is urgent to study the distortion signal recognition method suitable for the electric vehicle DC charging. Focusing on the characteristics of fundamental and ripple in DC charging signal, the Kalman filter algorithm is used to establish the matrix model, and the state variable method is introduced into the filter algorithm to track the parameter state, and the amplitude and phase of the fundamental waves and each secondary ripple are identified; In view of the time-varying characteristics of the unsteady and abrupt signal in the DC charging signal, the stratification and threshold parameters of the wavelet transform are corrected, and a multi-resolution method is established to identify and separate the unsteady and abrupt signals. Identification method of DC charging distortion signal of electric vehicle based on Kalman/modified wavelet transform is used to decompose and identify the signal characteristics of the whole charging process. Experiment results demonstrate that the algorithm can accurately identify ripple, sudden change and unsteady wave during charging. It has higher signal to noise ratio and lower mean root mean square error.

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