“…Krishnamoorthi et al [ 33 ] have used a turbulence-padded chaotic map to generate the pseudo-random numbers. Their method increased the periodicity and chaotic behavior.…”
Section: Chaotic Mapsmentioning
confidence: 99%
“…e Microcontroller output results for Barnsley Fern discrete chaotic map implemented on Arduino Fig. 10 a Operational model of the turbulent padded chaotic map as shown by Krishnamoorthi et al [ 33 ]. Here a logistic map is used to form the root chaotic map of the arrangement of turbulence padded chaotic map.…”
Section: Chaotic Mapsmentioning
confidence: 99%
“… a Operational model of the turbulent padded chaotic map as shown by Krishnamoorthi et al [ 33 ]. Here a logistic map is used to form the root chaotic map of the arrangement of turbulence padded chaotic map.…”
Section: Chaotic Mapsmentioning
confidence: 99%
“…Fig. 10 a Operational model of the turbulent padded chaotic map as shown by Krishnamoorthi et al[33].Here a logistic map is used to form the root chaotic map of the arrangement of turbulence padded chaotic map. It's the first case showing how the lower dimensional chaotic maps can be proved computationally efficient than higher-order chaotic maps.…”
Because of the COVID-19 pandemic, most of the tasks have shifted to an online platform. Sectors such as e-commerce, sensitive multi-media transfer, online banking have skyrocketed. Because of this, there is an urgent need to develop highly secure algorithms which can not be hacked into by unauthorized users. The method which is the backbone for building encryption algorithms is the pseudo-random number generator based on chaotic maps. Chaotic maps are mathematical functions that generate a highly arbitrary pattern based on the initial seed value. This manuscript gives a summary of how the chaotic maps are used to generate pseudo-random numbers and perform multimedia encryption. After carefully analyzing all the recent literature, we found that the lowest correlation coefficient was 0.00006, which was achieved by Ikeda chaotic map. The highest entropy was 7.999995 bits per byte using the quantum chaotic map. The lowest execution time observed was 0.23 seconds with the Zaslavsky chaotic map and the highest data rate was 15.367 Mbits per second using a hyperchaotic map. Chaotic map-based pseudo-random number generation can be utilized in multi-media encryption, video-game animations, digital marketing, chaotic system simulation, chaotic missile systems, and other applications.
“…Krishnamoorthi et al [ 33 ] have used a turbulence-padded chaotic map to generate the pseudo-random numbers. Their method increased the periodicity and chaotic behavior.…”
Section: Chaotic Mapsmentioning
confidence: 99%
“…e Microcontroller output results for Barnsley Fern discrete chaotic map implemented on Arduino Fig. 10 a Operational model of the turbulent padded chaotic map as shown by Krishnamoorthi et al [ 33 ]. Here a logistic map is used to form the root chaotic map of the arrangement of turbulence padded chaotic map.…”
Section: Chaotic Mapsmentioning
confidence: 99%
“… a Operational model of the turbulent padded chaotic map as shown by Krishnamoorthi et al [ 33 ]. Here a logistic map is used to form the root chaotic map of the arrangement of turbulence padded chaotic map.…”
Section: Chaotic Mapsmentioning
confidence: 99%
“…Fig. 10 a Operational model of the turbulent padded chaotic map as shown by Krishnamoorthi et al[33].Here a logistic map is used to form the root chaotic map of the arrangement of turbulence padded chaotic map. It's the first case showing how the lower dimensional chaotic maps can be proved computationally efficient than higher-order chaotic maps.…”
Because of the COVID-19 pandemic, most of the tasks have shifted to an online platform. Sectors such as e-commerce, sensitive multi-media transfer, online banking have skyrocketed. Because of this, there is an urgent need to develop highly secure algorithms which can not be hacked into by unauthorized users. The method which is the backbone for building encryption algorithms is the pseudo-random number generator based on chaotic maps. Chaotic maps are mathematical functions that generate a highly arbitrary pattern based on the initial seed value. This manuscript gives a summary of how the chaotic maps are used to generate pseudo-random numbers and perform multimedia encryption. After carefully analyzing all the recent literature, we found that the lowest correlation coefficient was 0.00006, which was achieved by Ikeda chaotic map. The highest entropy was 7.999995 bits per byte using the quantum chaotic map. The lowest execution time observed was 0.23 seconds with the Zaslavsky chaotic map and the highest data rate was 15.367 Mbits per second using a hyperchaotic map. Chaotic map-based pseudo-random number generation can be utilized in multi-media encryption, video-game animations, digital marketing, chaotic system simulation, chaotic missile systems, and other applications.
“…Some binarization techniques, 9‐11 may not always generate random sequences. To enhance the randomness many researchers have used multiple chaotic maps 18‐20 or multidimensional chaotic maps 21,22 . Similarly, random CEC points are also used in key sequence generation 23‐26 .…”
The chaotic functions and cyclic elliptic curves (CEC) has attracted many researchers, especially cryptographers, since decades. As CEC and chaotic functions meet the requirements of the cryptography, they are widely used either in key sequence generation or encryption/decryption process. Since in symmetric key encryption, stream ciphers need a large key sequence to encrypt/decrypt the information, authors propose a hybrid model to generate pseudo random sequence using CEC and logistic map. The hybrid model is developed using CEC points over GF(2 8 ) and an one-dimensional logistic map. In the proposed system, binary chaotic sequence and CEC points are given to AES S-box to get two random sequences separately. Byte wise parity is computed for both the sequences. Based on the parity of both the bytes, one of the byte is left shifted and the other is right shifted by two positions in a circular manner. Later, both the bytes are combined using the XOR operation to get the random binary sequence. The generated sequences are analysed for randomness using various test suites like NIST, Correlation, FIPS, and TestU01. It has been observed that all the sequences pass the randomness tests. Using additive stream cipher, image encryption is implemented by considering the generated sequence as key sequence. The performance evaluation and security analysis of the encryption process is conducted. The results obtained for the proposed system indicate that the system is robust to withstand many cryptanalytic attacks.
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