In this paper, a new algorithm for image encryption is proposed based on three chaotic systems which are Chen system,logistic map and two-dimensional (2D) Arnold cat map. First, a permutation scheme is applied to the image, and then shuffled image is partitioned into blocks of pixels. For each block, Chen system is employed for confusion and then logistic map is employed for generating subsititution-box (S-box) to substitute image blocks. The S-box is dynamic, where it is shuffled for each image block using permutation operation. Then, 2D Arnold cat map is used for providing diffusion, after that XORing the result using Chen system to obtain the encrypted image.The high security of proposed algorithm is experimented using histograms, unified average changing intensity (UACI), number of pixels change rate (NPCR), entropy, correlation and keyspace analyses.
Image confusion and diffusion based on multi-chaotic system and mix-columnjournalBEEI
In this paper, a new image encryption algorithm based on chaotic cryptography was proposed. The proposed scheme was based on multiple stages of confusion and diffusion. The diffusion process was implemented twice, first, by permuting the pixels of the plain image by using an Arnold cat map and, the second time by permuting the plain image pixels via the proposed permutation algorithm. The confusion process was performed many times, by performing the XOR operation between the two resulted from permuted images, subtracted a random value from all pixels of the image, as well as by implementing the mix column on the resulted image, and by used the Lorenz key to obtain the encrypted image. The security analysis tests that used to exam the results of this encryption method were information entropy, key space analysis, correlation, histogram analysis UACI, and NPCR have shown that the suggested algorithm has been resistant against different types of attacks.
Semantic Video Segmentation with Using Ensemble of Particular Classifiers and...ITIIIndustries
A new approach based on the use of a deep neural network and an ensemble of particular classifiers is proposed. This approach is based on use of the novel block of fuzzy generalization for combines classes of objects into semantic groups, each of which corresponds to one or more particular classifiers. As result of processing, the sequence of frames is converted into the annotation of the event occurring in the video for a certain time interval
Image Segmentation Using Two Weighted Variable Fuzzy K MeansEditor IJCATR
Image segmentation is the first step in image analysis and pattern recognition. Image segmentation is the process of dividing an image into different regions such that each region is homogeneous. The accurate and effective algorithm for segmenting image is very useful in many fields, especially in medical image. This paper presents a new approach for image segmentation by applying k-means algorithm with two level variable weighting. In image segmentation, clustering algorithms are very popular as they are intuitive and are also easy to implement. The K-means and Fuzzy k-means clustering algorithm is one of the most widely used algorithms in the literature, and many authors successfully compare their new proposal with the results achieved by the k-Means and Fuzzy k-Means. This paper proposes a new clustering algorithm called TW-fuzzy k-means, an automated two-level variable weighting clustering algorithm for segmenting object. In this algorithm, a variable weight is also assigned to each variable on the current partition of data. This could be applied on general images and/or specific images (i.e., medical and microscopic images). The proposed TW-Fuzzy k-means algorithm in terms of providing a better segmentation performance for various type of images. Based on the results obtained, the proposed algorithm gives better visual quality as compared to several other clustering methods.
DETECTION OF DENSE, OVERLAPPING, GEOMETRIC OBJECTSijaia
Using a unique data collection, we are able to study the detection of dense geometric objects in image data where object density, clarity, and size vary. The data is a large set of black and white images of scatterplots, taken from journals reporting thermophysical property data of metal systems, whose plot points are represented primarily by circles, triangles, and squares. We built a highly accurate single class U-Net convolutional neural network model to identify 97 % of image objects in a defined set of test images, locating the centers of the objects to within a few pixels of the correct locations. We found an optimal way in which to mark our training data masks to achieve this level of accuracy. The optimal markings for object classification, however, required more information in the masks to identify particular types of geometries. We show a range of different patterns used to mark the training data masks, and how they help or hurt our dual goals of location and classification. Altering the annotations in the segmentation masks can increase both the accuracy of object classification and localization on the plots, more than other factors such as
adding loss terms to the network calculations. However, localization of the plot points and classification of the geometric objects require different optimal training data.
This document presents a survey of contemporary research on image segmentation through clustering techniques. It discusses various clustering approaches including exclusive clustering (e.g. k-means), overlapping clustering (e.g. fuzzy c-means), hierarchical clustering, and probabilistic D-clustering. It provides details on the algorithms and steps involved in each technique. The paper analyzes different clustering methods for image segmentation and concludes that fuzzy c-means is superior but has high computational costs, while probabilistic D-clustering can avoid this issue.
IRJET- Finding Dominant Color in the Artistic Painting using Data Mining ...IRJET Journal
This document discusses finding the dominant color in an artistic painting using data mining techniques. It proposes using k-means clustering via the OpenCV library in Python to cluster pixels in the image by color and determine the dominant color cluster. The document provides background on k-means clustering and other clustering algorithms. It then describes applying a faster k-means algorithm to the image pixels to efficiently identify the dominant color in 2-3 times fewer iterations than standard k-means. The proposed system architecture involves preprocessing the image, extracting pixel vectors, clustering the pixels into color groups using fast k-means, and identifying the dominant color cluster.
Chaos Image Encryption using Pixel shuffling cscpconf
This document proposes a chaos-based image encryption algorithm using pixel shuffling. It uses elements from a chaotic map like the Henon map or Lorentz map to shuffle the pixel positions of an image. The chaotic elements are divided into blocks corresponding to the RGB channels. Pixel positions are reordered according to the sorted indices of each block. Encryption scrambles the pixel positions, while decryption restores the original positions using the same chaotic map. Experimental results on brain and Lena images show the encrypted images have very low correlation with the originals. Slight key changes also result in completely different decryptions, demonstrating key sensitivity of the algorithm.
Kernel based similarity estimation and real time tracking of movingIAEME Publication
This document discusses kernel-based mean shift algorithm for real-time object tracking. It presents the following:
1) The algorithm uses kernel density estimation to calculate the similarity between a target model and candidate windows, using the Bhattacharyya coefficient. 2) It can successfully track objects moving uniformly at slow speeds but struggles with fast or non-uniform motion, or changes in scale. 3) The algorithm was tested on video streams and could track objects moving slowly but failed for fast or irregular motion. Adaptive target windows are needed to handle changes in scale.
Image confusion and diffusion based on multi-chaotic system and mix-columnjournalBEEI
In this paper, a new image encryption algorithm based on chaotic cryptography was proposed. The proposed scheme was based on multiple stages of confusion and diffusion. The diffusion process was implemented twice, first, by permuting the pixels of the plain image by using an Arnold cat map and, the second time by permuting the plain image pixels via the proposed permutation algorithm. The confusion process was performed many times, by performing the XOR operation between the two resulted from permuted images, subtracted a random value from all pixels of the image, as well as by implementing the mix column on the resulted image, and by used the Lorenz key to obtain the encrypted image. The security analysis tests that used to exam the results of this encryption method were information entropy, key space analysis, correlation, histogram analysis UACI, and NPCR have shown that the suggested algorithm has been resistant against different types of attacks.
Semantic Video Segmentation with Using Ensemble of Particular Classifiers and...ITIIIndustries
A new approach based on the use of a deep neural network and an ensemble of particular classifiers is proposed. This approach is based on use of the novel block of fuzzy generalization for combines classes of objects into semantic groups, each of which corresponds to one or more particular classifiers. As result of processing, the sequence of frames is converted into the annotation of the event occurring in the video for a certain time interval
Image Segmentation Using Two Weighted Variable Fuzzy K MeansEditor IJCATR
Image segmentation is the first step in image analysis and pattern recognition. Image segmentation is the process of dividing an image into different regions such that each region is homogeneous. The accurate and effective algorithm for segmenting image is very useful in many fields, especially in medical image. This paper presents a new approach for image segmentation by applying k-means algorithm with two level variable weighting. In image segmentation, clustering algorithms are very popular as they are intuitive and are also easy to implement. The K-means and Fuzzy k-means clustering algorithm is one of the most widely used algorithms in the literature, and many authors successfully compare their new proposal with the results achieved by the k-Means and Fuzzy k-Means. This paper proposes a new clustering algorithm called TW-fuzzy k-means, an automated two-level variable weighting clustering algorithm for segmenting object. In this algorithm, a variable weight is also assigned to each variable on the current partition of data. This could be applied on general images and/or specific images (i.e., medical and microscopic images). The proposed TW-Fuzzy k-means algorithm in terms of providing a better segmentation performance for various type of images. Based on the results obtained, the proposed algorithm gives better visual quality as compared to several other clustering methods.
DETECTION OF DENSE, OVERLAPPING, GEOMETRIC OBJECTSijaia
Using a unique data collection, we are able to study the detection of dense geometric objects in image data where object density, clarity, and size vary. The data is a large set of black and white images of scatterplots, taken from journals reporting thermophysical property data of metal systems, whose plot points are represented primarily by circles, triangles, and squares. We built a highly accurate single class U-Net convolutional neural network model to identify 97 % of image objects in a defined set of test images, locating the centers of the objects to within a few pixels of the correct locations. We found an optimal way in which to mark our training data masks to achieve this level of accuracy. The optimal markings for object classification, however, required more information in the masks to identify particular types of geometries. We show a range of different patterns used to mark the training data masks, and how they help or hurt our dual goals of location and classification. Altering the annotations in the segmentation masks can increase both the accuracy of object classification and localization on the plots, more than other factors such as
adding loss terms to the network calculations. However, localization of the plot points and classification of the geometric objects require different optimal training data.
This document presents a survey of contemporary research on image segmentation through clustering techniques. It discusses various clustering approaches including exclusive clustering (e.g. k-means), overlapping clustering (e.g. fuzzy c-means), hierarchical clustering, and probabilistic D-clustering. It provides details on the algorithms and steps involved in each technique. The paper analyzes different clustering methods for image segmentation and concludes that fuzzy c-means is superior but has high computational costs, while probabilistic D-clustering can avoid this issue.
IRJET- Finding Dominant Color in the Artistic Painting using Data Mining ...IRJET Journal
This document discusses finding the dominant color in an artistic painting using data mining techniques. It proposes using k-means clustering via the OpenCV library in Python to cluster pixels in the image by color and determine the dominant color cluster. The document provides background on k-means clustering and other clustering algorithms. It then describes applying a faster k-means algorithm to the image pixels to efficiently identify the dominant color in 2-3 times fewer iterations than standard k-means. The proposed system architecture involves preprocessing the image, extracting pixel vectors, clustering the pixels into color groups using fast k-means, and identifying the dominant color cluster.
Chaos Image Encryption using Pixel shuffling cscpconf
This document proposes a chaos-based image encryption algorithm using pixel shuffling. It uses elements from a chaotic map like the Henon map or Lorentz map to shuffle the pixel positions of an image. The chaotic elements are divided into blocks corresponding to the RGB channels. Pixel positions are reordered according to the sorted indices of each block. Encryption scrambles the pixel positions, while decryption restores the original positions using the same chaotic map. Experimental results on brain and Lena images show the encrypted images have very low correlation with the originals. Slight key changes also result in completely different decryptions, demonstrating key sensitivity of the algorithm.
Kernel based similarity estimation and real time tracking of movingIAEME Publication
This document discusses kernel-based mean shift algorithm for real-time object tracking. It presents the following:
1) The algorithm uses kernel density estimation to calculate the similarity between a target model and candidate windows, using the Bhattacharyya coefficient. 2) It can successfully track objects moving uniformly at slow speeds but struggles with fast or non-uniform motion, or changes in scale. 3) The algorithm was tested on video streams and could track objects moving slowly but failed for fast or irregular motion. Adaptive target windows are needed to handle changes in scale.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An enhanced fireworks algorithm to generate prime key for multiple users in f...journalBEEI
This work presents a new method to enhance the performance of fireworks algorithm to generate a prime key for multiple users. A threshold technique in image segmentation is used as one of the major steps. It is used processing the digital image. Some useful algorithms and methods for dividing and sharing an image, including measuring, recognizing, and recognizing, are common. In this research, we proposed a hybrid technique of fireworks and camel herd algorithms (HFCA), where Fireworks are based on 3-dimension (3D) logistic chaotic maps. Both, the Otsu method and the convolution technique are used in the pre-processing image for further analysis. The Otsu is employed to segment the image and find the threshold for each image, and convolution is used to extract the features of the used images. The sample of the images consists of two images of fingerprints taken from the Biometric System Lab (University of Bologna). The performance of the anticipated method is evaluated by using FVC2004 dataset. The results of the work enhanced algorithm, so quick response code (QRcode) is used to generate a stream key by using random text or number, which is a class of symmetric-key algorithm that operates on individual bits or bytes.
IMAGE ENCRYPTION BASED ON DIFFUSION AND MULTIPLE CHAOTIC MAPSIJNSA Journal
This document proposes an image encryption algorithm that uses diffusion and multiple chaotic maps. It begins by generating subkeys using chaotic logistic maps. The image is then encrypted using one subkey via logistic map transformation, diffusing the image. Additional subkeys are generated from four chaotic maps by hopping through various map orbits. The image is treated as a 1D array via raster and zigzag scanning, divided into blocks, and those blocks undergo position permutation and value transformation controlled by the chaotic subkeys, fully encrypting the image. Decryption reverses the process using the same subkeys.
The document discusses the applicability of fuzzy theory in remote sensing image classification. It presents three experiments comparing different classification methods: 1) Unsupervised fuzzy c-means classification, 2) Supervised classification using fuzzy signatures, 3) Supervised classification using fuzzy signatures and membership functions. The supervised fuzzy methods achieved higher accuracy than the unsupervised method, with the third method performing best with an overall accuracy of 83.9%. Fuzzy convolution can further optimize results by combining classification bands.
Encryption-Decryption RGB Color Image Using Matrix Multiplicationijcsit
An enhanced technique of color image encryption based on random matrix key encoding is proposed. To
encrypt the color image a separation into Red Green and Blue (R, G, B) channels will applied. Each
channel is encrypted using a technique called double random matrix key encoding then three new coding
image matrices are constructed. To obtain the reconstructed image that is the same as the original image
in the receipted side; simple extracted and decryption operations can be maintained. The results shown
that the proposed technique is powerful for color image encryption and decryption and a MATLAB and
simulations were used to get the results.
The proposed technique has high security features because each color component is separately treated
using its own double random matrix key which is generated randomly and make the process of hacking the
three keys very difficult.
Chaos Image Encryption Methods: A Survey StudyjournalBEEI
This document surveys various chaos encryption techniques for encrypting image data. It begins by explaining why traditional encryption techniques are unsuitable for images and how chaos encryption provides an effective solution. It then provides background on chaos theory and describes the general process of chaos-based image encryption. The document proceeds to summarize several specific chaos encryption algorithms proposed in other papers, evaluating aspects like key space, correlation coefficient, and resistance to attacks. It concludes that chaos encryption is an effective method for secure image encryption and multiple techniques can be combined to further increase security.
INTRA BLOCK AND INTER BLOCK NEIGHBORING JOINT DENSITY BASED APPROACH FOR JPEG...ijsc
Steganalysis is the method used to detect the presence of any hidden message in a cover medium. A novel
approach based on feature mining on the discrete cosine transform (DCT) domain based approach,
machine learning for steganalysis of JPEG images is proposed. The neighboring joint density on both
intra-block and inter-block are extracted from the DCT coefficient array. After the feature space has been
constructed, it uses SVM like binary classifier for training and classification. The performance of the
proposed method on different Steganographic systems named F5, Pixel Value Differencing, Model Based
Steganography with and without deblocking, JPHS, Steghide etc are analyzed. Individually each feature
and combined features classification accuracy is checked and concludes which provides better
classification.
This document summarizes a research paper about developing a new set of low-complexity features for detecting steganography in JPEG images. The proposed features, called DCTR features, are computed by taking the discrete cosine transform (DCT) of non-overlapping 8x8 blocks of the image, resulting in 64 feature maps. Histograms are formed from the quantized noise residuals in these feature maps. This approach has lower computational complexity than previous rich models used for steganalysis and provides competitive detection accuracy across different steganographic algorithms while using fewer features. The paper introduces the concept of an undecimated DCT and explains how it relates to previous work in JPEG steganalysis.
METHOD FOR A SIMPLE ENCRYPTION OF IMAGES BASED ON THE CHAOTIC MAP OF BERNOULLIijcsit
In this document, we propose a simple algorithm for the encryption of gray-scale images, although the
scheme is perfectly usable in color images. Prior to encryption, the proposed algorithm includes a pair of
permutation processes, inspired by the Bernoulli mapping. The permutation disperses the image
information to hinder the unauthorized recovery of the original image. The image is encrypted using the
XOR function between a sequence generated from the same Bernoulli mapping and the image data,
obtained after two permutation processes. Finally, for the verification of the algorithm, the gray-scale Lena
pattern image was used; calculating histograms for each stage alongside of the encryption process. The
histograms prove dispersion evolution for pattern image during whole algorithm.
This document presents an improved multi-SOM clustering algorithm that uses the Davies-Bouldin index to determine the optimal number of clusters. The multi-SOM algorithm iteratively clusters an initial self-organizing map (SOM) grid using the DB index at each level until the index reaches its minimum value, indicating the best number of clusters. Experimental results on five datasets show the proposed algorithm performs as well as or better than k-means, BIRCH, and a previous multi-SOM algorithm in determining the correct number of clusters.
This paper presents an FPGA-based algorithm for moving object detection from video for traffic surveillance. The algorithm uses background subtraction, edge detection and shadow detection techniques. Background subtraction involves selective and non-selective updating to improve sensitivity. Edge detection helps find object boundaries while shadow detection removes falsely detected pixels from shadows. The algorithm is implemented using VHDL on a Spartan-6 FPGA board. Experimental results show the algorithm can accurately detect moving vehicles in different lighting conditions with low power consumption, making it suitable for traffic monitoring applications.
A FRACTAL BASED IMAGE CIPHER USING KNUTH SHUFFLE METHOD AND DYNAMIC DIFFUSIONIJCNCJournal
This paper proposes a fractal-based image encryption algorithm which follows permutation-substitution structure to maintain confusion and diffusion properties. The scheme consists of three phases: key generation process; pixel permutation using the Knuth shuffle method; and the dynamic diffusion of scrambled image. A burning ship fractal function is employed to generate a secret key sequence which is further scanned using the Hilbert transformation method to increase the randomness. The chaotic behavior of the fractal strengthens the key sensitivity towards its initial condition. In the permutation phase, the Knuth shuffle method is applied to a noisy plain image to change the index value of each pixel. To substitute the pixel values, a dynamic diffusion is suggested in which each scrambled pixel change its value by using the current key pixel and the previously ciphered image pixel. To enhance the security of the cryptosystem, the secret key is also modified at each encryption step by performing algebraic transformations. The visual and numerical analysis demonstrates that the proposed scheme is reliable to secure transmission of gray as well as color images.
This document presents a novel method for recognizing two-dimensional QR barcodes using texture feature analysis and neural networks. It first extracts texture features like mean, standard deviation, smoothness, skewness and entropy from divided blocks of barcode images. These features are then used to train a neural network to classify blocks as containing a barcode or not. The trained neural network can then be used to locate barcodes in unknown images by classifying each block. The method is implemented and evaluated using MATLAB on a database of QR code images, showing satisfactory recognition results.
A novel method is proposed for image segmentation based on probabilistic field theory. This model assumes that the whole pixels of an image and some unknown parameters form a field. According to this model, the pixel labels are generated by a compound function of the field. The main novelty of this model is it consider the features of the pixels and the interdependent among the pixels. The parameters are generated by a novel spatially variant mixture model and estimated by expectation-maximization (EM)-
based algorithm. Thus, we simultaneously impose the spatial smoothness on the prior knowledge. Numerical experiments are presented where the proposed method and other mixture model-based methods were tested on synthetic and real world images. These experimental results demonstrate that our algorithm achieves competitive performance compared to other methods.
COLOR IMAGE ENCRYPTION BASED ON MULTIPLE CHAOTIC SYSTEMSIJNSA Journal
This paper proposed a novel color image encryption scheme based on multiple chaotic systems. The ergodicity property of chaotic system is utilized to perform the permutation process; a substitution
operation is applied to achieve the diffusion effect. In permutation stage, the 3D color plain-image matrix
is converted to a 2D image matrix, then two generalized Arnold maps are employed to generate hybrid chaotic sequences which are dependent on the plain-image’s content. The generated chaotic sequences are then applied to perform the permutation process. The encryption’s key streams not only depend on the
cipher keys but also depend on plain-image and therefore can resist chosen-plaintext attack as well as
known-plaintext attack. In the diffusion stage, four pseudo-random gray value sequences are generated by another generalized Arnold map. The gray value sequences are applied to perform the diffusion process by bitxoring operation with the permuted image row-by-row or column-by-column to improve the encryption rate. The security and performance analysis have been performed, including key space analysis, histogram analysis, correlation analysis, information entropy analysis, key sensitivity analysis, differential analysis etc. The experimental results show that the proposed image encryption scheme is highly secure thanks to its large key space and efficient permutation-substitution operation, and therefore it is suitable for practical image and video encryption.
COLOR IMAGE ENCRYPTION BASED ON MULTIPLE CHAOTIC SYSTEMSIJNSA Journal
This paper proposed a novel color image encryption scheme based on multiple chaotic systems. The ergodicity property of chaotic system is utilized to perform the permutation process; a substitution operation is applied to achieve the diffusion effect. In permutation stage, the 3D color plain-image matrix is converted to a 2D image matrix, then two generalized Arnold maps are employed to generate hybrid chaotic sequences which are dependent on the plain-image’s content. The generated chaotic sequences are then applied to perform the permutation process. The encryption’s key streams not only depend on the cipher keys but also depend on plain-image and therefore can resist chosen-plaintext attack as well as
known-plaintext attack. In the diffusion stage, four pseudo-random gray value sequences are generated by
another generalized Arnold map. The gray value sequences are applied to perform the diffusion process by bitxoring operation with the permuted image row-by-row or column-by-column to improve the encryption rate. The security and performance analysis have been performed, including key space analysis, histogram analysis, correlation analysis, information entropy analysis, key sensitivity analysis, differential analysis
etc. The experimental results show that the proposed image encryption scheme is highly secure thanks to its
large key space and efficient permutation-substitution operation, and therefore it is suitable for practical image and video encryption.
COLOR IMAGE ENCRYPTION BASED ON MULTIPLE CHAOTIC SYSTEMSIJNSA Journal
This document proposes a novel color image encryption scheme based on multiple chaotic systems. The scheme utilizes the ergodic properties of chaotic systems to perform pixel permutation and applies a substitution operation to achieve diffusion. In the permutation stage, two generalized Arnold maps are used to generate hybrid chaotic sequences to permute pixel positions. In the diffusion stage, four pseudo-random gray value sequences generated by another generalized Arnold map are used to diffuse the permuted image via bitwise XOR operations. Security analysis shows the scheme has a large key space and is highly secure against statistical attacks, differential attacks, and chosen/known plaintext attacks.
This document proposes a medical image encryption technique that uses multiple chaotic maps. It utilizes the logistic map, Arnold cat map, and Baker's map within a triple data encryption standard (3DES) scheme. The technique encrypts and decrypts medical images efficiently and securely, making it suitable for transmission over insecure networks. It was tested using the transmission control protocol (TCP)/internet protocol (IP) to transfer encrypted images between a server and client. Experimental results found the method resistant to attacks while maintaining encryption performance.
A new four-dimensional hyper-chaotic system for image encryption IJECEIAES
Currently, images are very important with the rapid growth of communication networks. Therefore, image encryption is a process to provide security for private information and prevent unwanted access to sensitive data by unauthorized individuals. Chaos systems provide an important role for key generation, with high randomization properties and accurate performance. In this study, a new four-dimensional hyper-chaotic system has been suggested that is used in the keys generation, which are utilized in the image encryption process to achieve permutation and substitution operations. Firstly, color bands are permuted using the index of the chaotic sequences to remove the high correlation among neighboring pixels. Secondly, dynamic S-boxes achieve the principle of substitution, which are utilized to diffuse the pixel values of the color image. The efficiency of the proposed method is tested by the key space, histogram, and so on. Security analysis shows that the proposed method for encrypting images is secure and resistant to different attacks. It contains a big key space of (2627) and a high sensitivity to a slight change in the secret key, a fairly uniform histogram, and entropy values nearby to the best value of 8. Moreover, it consumes a very short time for encryption and decryption.
Enhancement and Analysis of Chaotic Image Encryption Algorithms cscpconf
The focus of this paper is to improve the level of security and secrecy provided by the chaotic
map based image encryption.An encryption algorithm based on the Logistic and the Henon
maps is proposed. The algorithm uses chaotic iteration to generate the encryption keys, and
then carries out the XOR and cyclic shift operations on the plain text to change the values of
image pixels. Chaotic Map Lattice based image encryption algorithm suggested by Pisarchik is
also examined which is based on Logistic map alone. In experiments, the corresponding results
showed the proposed method is a promising scheme for image encryption in terms of security
and secrecy. At the end, we show the results of a security analysis and a comparison of both
schemes
Chaotic Block Image Scheme using Large Key Space and Message Digest AlgorithmCSCJournals
In this paper, chaotic block image scheme using large key space and message digest algorithm. Cat map intended for confusion and 2D-Sine Tent Composite map (2D-STCM) key generator intended for diffusion. Confusion is implemented by 2D Cat map with arbitrary block size. In the first tendency, 2D cat map use for local shuffling of indexes inside blocks, while in the second tendency, 2D cat map used for global shuffling of whole image indexes. The designed algorithm executes two confusions and one diffusion in each iteration. To increase the security level, the message digestion algorithm is used as a fingerprint for the plain image that creates the initial value of the key. After that 2D-STCM generates a large key stream. Diffusion implementation takes place by XOR operation; between a key stream and confused image. Experimental results, show that security level increases due to integration of confusion and diffusion. On the other side large key space and the high sensitivity of secret keys have been given a guarantee for the performance of the security. Performance measures reach to the top value among those in the similar researches. To verify the obtained results, authors implemented inverse chaos. All the tests are processed by MATLAB 2015a.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An enhanced fireworks algorithm to generate prime key for multiple users in f...journalBEEI
This work presents a new method to enhance the performance of fireworks algorithm to generate a prime key for multiple users. A threshold technique in image segmentation is used as one of the major steps. It is used processing the digital image. Some useful algorithms and methods for dividing and sharing an image, including measuring, recognizing, and recognizing, are common. In this research, we proposed a hybrid technique of fireworks and camel herd algorithms (HFCA), where Fireworks are based on 3-dimension (3D) logistic chaotic maps. Both, the Otsu method and the convolution technique are used in the pre-processing image for further analysis. The Otsu is employed to segment the image and find the threshold for each image, and convolution is used to extract the features of the used images. The sample of the images consists of two images of fingerprints taken from the Biometric System Lab (University of Bologna). The performance of the anticipated method is evaluated by using FVC2004 dataset. The results of the work enhanced algorithm, so quick response code (QRcode) is used to generate a stream key by using random text or number, which is a class of symmetric-key algorithm that operates on individual bits or bytes.
IMAGE ENCRYPTION BASED ON DIFFUSION AND MULTIPLE CHAOTIC MAPSIJNSA Journal
This document proposes an image encryption algorithm that uses diffusion and multiple chaotic maps. It begins by generating subkeys using chaotic logistic maps. The image is then encrypted using one subkey via logistic map transformation, diffusing the image. Additional subkeys are generated from four chaotic maps by hopping through various map orbits. The image is treated as a 1D array via raster and zigzag scanning, divided into blocks, and those blocks undergo position permutation and value transformation controlled by the chaotic subkeys, fully encrypting the image. Decryption reverses the process using the same subkeys.
The document discusses the applicability of fuzzy theory in remote sensing image classification. It presents three experiments comparing different classification methods: 1) Unsupervised fuzzy c-means classification, 2) Supervised classification using fuzzy signatures, 3) Supervised classification using fuzzy signatures and membership functions. The supervised fuzzy methods achieved higher accuracy than the unsupervised method, with the third method performing best with an overall accuracy of 83.9%. Fuzzy convolution can further optimize results by combining classification bands.
Encryption-Decryption RGB Color Image Using Matrix Multiplicationijcsit
An enhanced technique of color image encryption based on random matrix key encoding is proposed. To
encrypt the color image a separation into Red Green and Blue (R, G, B) channels will applied. Each
channel is encrypted using a technique called double random matrix key encoding then three new coding
image matrices are constructed. To obtain the reconstructed image that is the same as the original image
in the receipted side; simple extracted and decryption operations can be maintained. The results shown
that the proposed technique is powerful for color image encryption and decryption and a MATLAB and
simulations were used to get the results.
The proposed technique has high security features because each color component is separately treated
using its own double random matrix key which is generated randomly and make the process of hacking the
three keys very difficult.
Chaos Image Encryption Methods: A Survey StudyjournalBEEI
This document surveys various chaos encryption techniques for encrypting image data. It begins by explaining why traditional encryption techniques are unsuitable for images and how chaos encryption provides an effective solution. It then provides background on chaos theory and describes the general process of chaos-based image encryption. The document proceeds to summarize several specific chaos encryption algorithms proposed in other papers, evaluating aspects like key space, correlation coefficient, and resistance to attacks. It concludes that chaos encryption is an effective method for secure image encryption and multiple techniques can be combined to further increase security.
INTRA BLOCK AND INTER BLOCK NEIGHBORING JOINT DENSITY BASED APPROACH FOR JPEG...ijsc
Steganalysis is the method used to detect the presence of any hidden message in a cover medium. A novel
approach based on feature mining on the discrete cosine transform (DCT) domain based approach,
machine learning for steganalysis of JPEG images is proposed. The neighboring joint density on both
intra-block and inter-block are extracted from the DCT coefficient array. After the feature space has been
constructed, it uses SVM like binary classifier for training and classification. The performance of the
proposed method on different Steganographic systems named F5, Pixel Value Differencing, Model Based
Steganography with and without deblocking, JPHS, Steghide etc are analyzed. Individually each feature
and combined features classification accuracy is checked and concludes which provides better
classification.
This document summarizes a research paper about developing a new set of low-complexity features for detecting steganography in JPEG images. The proposed features, called DCTR features, are computed by taking the discrete cosine transform (DCT) of non-overlapping 8x8 blocks of the image, resulting in 64 feature maps. Histograms are formed from the quantized noise residuals in these feature maps. This approach has lower computational complexity than previous rich models used for steganalysis and provides competitive detection accuracy across different steganographic algorithms while using fewer features. The paper introduces the concept of an undecimated DCT and explains how it relates to previous work in JPEG steganalysis.
METHOD FOR A SIMPLE ENCRYPTION OF IMAGES BASED ON THE CHAOTIC MAP OF BERNOULLIijcsit
In this document, we propose a simple algorithm for the encryption of gray-scale images, although the
scheme is perfectly usable in color images. Prior to encryption, the proposed algorithm includes a pair of
permutation processes, inspired by the Bernoulli mapping. The permutation disperses the image
information to hinder the unauthorized recovery of the original image. The image is encrypted using the
XOR function between a sequence generated from the same Bernoulli mapping and the image data,
obtained after two permutation processes. Finally, for the verification of the algorithm, the gray-scale Lena
pattern image was used; calculating histograms for each stage alongside of the encryption process. The
histograms prove dispersion evolution for pattern image during whole algorithm.
This document presents an improved multi-SOM clustering algorithm that uses the Davies-Bouldin index to determine the optimal number of clusters. The multi-SOM algorithm iteratively clusters an initial self-organizing map (SOM) grid using the DB index at each level until the index reaches its minimum value, indicating the best number of clusters. Experimental results on five datasets show the proposed algorithm performs as well as or better than k-means, BIRCH, and a previous multi-SOM algorithm in determining the correct number of clusters.
This paper presents an FPGA-based algorithm for moving object detection from video for traffic surveillance. The algorithm uses background subtraction, edge detection and shadow detection techniques. Background subtraction involves selective and non-selective updating to improve sensitivity. Edge detection helps find object boundaries while shadow detection removes falsely detected pixels from shadows. The algorithm is implemented using VHDL on a Spartan-6 FPGA board. Experimental results show the algorithm can accurately detect moving vehicles in different lighting conditions with low power consumption, making it suitable for traffic monitoring applications.
A FRACTAL BASED IMAGE CIPHER USING KNUTH SHUFFLE METHOD AND DYNAMIC DIFFUSIONIJCNCJournal
This paper proposes a fractal-based image encryption algorithm which follows permutation-substitution structure to maintain confusion and diffusion properties. The scheme consists of three phases: key generation process; pixel permutation using the Knuth shuffle method; and the dynamic diffusion of scrambled image. A burning ship fractal function is employed to generate a secret key sequence which is further scanned using the Hilbert transformation method to increase the randomness. The chaotic behavior of the fractal strengthens the key sensitivity towards its initial condition. In the permutation phase, the Knuth shuffle method is applied to a noisy plain image to change the index value of each pixel. To substitute the pixel values, a dynamic diffusion is suggested in which each scrambled pixel change its value by using the current key pixel and the previously ciphered image pixel. To enhance the security of the cryptosystem, the secret key is also modified at each encryption step by performing algebraic transformations. The visual and numerical analysis demonstrates that the proposed scheme is reliable to secure transmission of gray as well as color images.
This document presents a novel method for recognizing two-dimensional QR barcodes using texture feature analysis and neural networks. It first extracts texture features like mean, standard deviation, smoothness, skewness and entropy from divided blocks of barcode images. These features are then used to train a neural network to classify blocks as containing a barcode or not. The trained neural network can then be used to locate barcodes in unknown images by classifying each block. The method is implemented and evaluated using MATLAB on a database of QR code images, showing satisfactory recognition results.
A novel method is proposed for image segmentation based on probabilistic field theory. This model assumes that the whole pixels of an image and some unknown parameters form a field. According to this model, the pixel labels are generated by a compound function of the field. The main novelty of this model is it consider the features of the pixels and the interdependent among the pixels. The parameters are generated by a novel spatially variant mixture model and estimated by expectation-maximization (EM)-
based algorithm. Thus, we simultaneously impose the spatial smoothness on the prior knowledge. Numerical experiments are presented where the proposed method and other mixture model-based methods were tested on synthetic and real world images. These experimental results demonstrate that our algorithm achieves competitive performance compared to other methods.
COLOR IMAGE ENCRYPTION BASED ON MULTIPLE CHAOTIC SYSTEMSIJNSA Journal
This paper proposed a novel color image encryption scheme based on multiple chaotic systems. The ergodicity property of chaotic system is utilized to perform the permutation process; a substitution
operation is applied to achieve the diffusion effect. In permutation stage, the 3D color plain-image matrix
is converted to a 2D image matrix, then two generalized Arnold maps are employed to generate hybrid chaotic sequences which are dependent on the plain-image’s content. The generated chaotic sequences are then applied to perform the permutation process. The encryption’s key streams not only depend on the
cipher keys but also depend on plain-image and therefore can resist chosen-plaintext attack as well as
known-plaintext attack. In the diffusion stage, four pseudo-random gray value sequences are generated by another generalized Arnold map. The gray value sequences are applied to perform the diffusion process by bitxoring operation with the permuted image row-by-row or column-by-column to improve the encryption rate. The security and performance analysis have been performed, including key space analysis, histogram analysis, correlation analysis, information entropy analysis, key sensitivity analysis, differential analysis etc. The experimental results show that the proposed image encryption scheme is highly secure thanks to its large key space and efficient permutation-substitution operation, and therefore it is suitable for practical image and video encryption.
COLOR IMAGE ENCRYPTION BASED ON MULTIPLE CHAOTIC SYSTEMSIJNSA Journal
This paper proposed a novel color image encryption scheme based on multiple chaotic systems. The ergodicity property of chaotic system is utilized to perform the permutation process; a substitution operation is applied to achieve the diffusion effect. In permutation stage, the 3D color plain-image matrix is converted to a 2D image matrix, then two generalized Arnold maps are employed to generate hybrid chaotic sequences which are dependent on the plain-image’s content. The generated chaotic sequences are then applied to perform the permutation process. The encryption’s key streams not only depend on the cipher keys but also depend on plain-image and therefore can resist chosen-plaintext attack as well as
known-plaintext attack. In the diffusion stage, four pseudo-random gray value sequences are generated by
another generalized Arnold map. The gray value sequences are applied to perform the diffusion process by bitxoring operation with the permuted image row-by-row or column-by-column to improve the encryption rate. The security and performance analysis have been performed, including key space analysis, histogram analysis, correlation analysis, information entropy analysis, key sensitivity analysis, differential analysis
etc. The experimental results show that the proposed image encryption scheme is highly secure thanks to its
large key space and efficient permutation-substitution operation, and therefore it is suitable for practical image and video encryption.
COLOR IMAGE ENCRYPTION BASED ON MULTIPLE CHAOTIC SYSTEMSIJNSA Journal
This document proposes a novel color image encryption scheme based on multiple chaotic systems. The scheme utilizes the ergodic properties of chaotic systems to perform pixel permutation and applies a substitution operation to achieve diffusion. In the permutation stage, two generalized Arnold maps are used to generate hybrid chaotic sequences to permute pixel positions. In the diffusion stage, four pseudo-random gray value sequences generated by another generalized Arnold map are used to diffuse the permuted image via bitwise XOR operations. Security analysis shows the scheme has a large key space and is highly secure against statistical attacks, differential attacks, and chosen/known plaintext attacks.
This document proposes a medical image encryption technique that uses multiple chaotic maps. It utilizes the logistic map, Arnold cat map, and Baker's map within a triple data encryption standard (3DES) scheme. The technique encrypts and decrypts medical images efficiently and securely, making it suitable for transmission over insecure networks. It was tested using the transmission control protocol (TCP)/internet protocol (IP) to transfer encrypted images between a server and client. Experimental results found the method resistant to attacks while maintaining encryption performance.
A new four-dimensional hyper-chaotic system for image encryption IJECEIAES
Currently, images are very important with the rapid growth of communication networks. Therefore, image encryption is a process to provide security for private information and prevent unwanted access to sensitive data by unauthorized individuals. Chaos systems provide an important role for key generation, with high randomization properties and accurate performance. In this study, a new four-dimensional hyper-chaotic system has been suggested that is used in the keys generation, which are utilized in the image encryption process to achieve permutation and substitution operations. Firstly, color bands are permuted using the index of the chaotic sequences to remove the high correlation among neighboring pixels. Secondly, dynamic S-boxes achieve the principle of substitution, which are utilized to diffuse the pixel values of the color image. The efficiency of the proposed method is tested by the key space, histogram, and so on. Security analysis shows that the proposed method for encrypting images is secure and resistant to different attacks. It contains a big key space of (2627) and a high sensitivity to a slight change in the secret key, a fairly uniform histogram, and entropy values nearby to the best value of 8. Moreover, it consumes a very short time for encryption and decryption.
Enhancement and Analysis of Chaotic Image Encryption Algorithms cscpconf
The focus of this paper is to improve the level of security and secrecy provided by the chaotic
map based image encryption.An encryption algorithm based on the Logistic and the Henon
maps is proposed. The algorithm uses chaotic iteration to generate the encryption keys, and
then carries out the XOR and cyclic shift operations on the plain text to change the values of
image pixels. Chaotic Map Lattice based image encryption algorithm suggested by Pisarchik is
also examined which is based on Logistic map alone. In experiments, the corresponding results
showed the proposed method is a promising scheme for image encryption in terms of security
and secrecy. At the end, we show the results of a security analysis and a comparison of both
schemes
Chaotic Block Image Scheme using Large Key Space and Message Digest AlgorithmCSCJournals
In this paper, chaotic block image scheme using large key space and message digest algorithm. Cat map intended for confusion and 2D-Sine Tent Composite map (2D-STCM) key generator intended for diffusion. Confusion is implemented by 2D Cat map with arbitrary block size. In the first tendency, 2D cat map use for local shuffling of indexes inside blocks, while in the second tendency, 2D cat map used for global shuffling of whole image indexes. The designed algorithm executes two confusions and one diffusion in each iteration. To increase the security level, the message digestion algorithm is used as a fingerprint for the plain image that creates the initial value of the key. After that 2D-STCM generates a large key stream. Diffusion implementation takes place by XOR operation; between a key stream and confused image. Experimental results, show that security level increases due to integration of confusion and diffusion. On the other side large key space and the high sensitivity of secret keys have been given a guarantee for the performance of the security. Performance measures reach to the top value among those in the similar researches. To verify the obtained results, authors implemented inverse chaos. All the tests are processed by MATLAB 2015a.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Image encryption algorithm based on the density and 6D logistic map IJECEIAES
One of the most difficult issues in the history of communication technology is the transmission of secure images. On the internet, photos are used and shared by millions of individuals for both private and business reasons. Utilizing encryption methods to change the original image into an unintelligible or scrambled version is one way to achieve safe image transfer over the network. Cryptographic approaches based on chaotic logistic theory provide several new and promising options for developing secure Image encryption methods. The main aim of this paper is to build a secure system for encrypting gray and color images. The proposed system consists of two stages, the first stage is the encryption process, in which the keys are generated depending on the chaotic logistic with the image density to encrypt the gray and color images, and the second stage is the decryption, which is the opposite of the encryption process to obtain the original image. The proposed method has been tested on two standard gray and color images publicly available. The test results indicate to the highest value of peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), number of pixel change rate (NPCR) are 7.7268, 50.2011 and 100, respectively. While the encryption and decryption speed up to 0.6319 and 0.5305 second respectively.
Today among various medium of data transmission or storage our sensitive data
are not secured with a third-party, that we used to take help of. Cryptography plays an
important role in securing our data from malicious attack. This paper present a partial
image encryption based on bit-planes permutation using Peter De Jong chaotic map for
secure image transmission and storage. The proposed partial image encryption is a raw data
encryption method where bits of some bit-planes are shuffled among other bit-planes based
on chaotic maps proposed by Peter De Jong. By using the chaotic behavior of the Peter De
Jong map the position of all the bit-planes are permuted. The result of the several
experimental, correlation analysis and sensitivity test shows that the proposed image
encryption scheme provides an efficient and secure way for real-time image encryption and
decryption.
Hybrid chaos-based image encryption algorithm using Chebyshev chaotic map wit...IJECEIAES
The media content shared on the internet has increased tremendously nowadays. The streaming service has major role in contributing to internet traffic all over the world. As the major content shared are in the form of images and rapid increase in computing power a better and complex encryption standard is needed to protect this data from being leaked to unauthorized person. Our proposed system makes use of chaotic maps, deoxyribonucleic acid (DNA) coding and ribonucleic acid (RNA) coding technique to encrypt the image. As videos are nothing but collection of images played at the rate of minimum 30 frames/images per second, this methodology can also be used to encrypt videos. The complexity and dynamic nature of chaotic systems makes decryption of content by unauthorized personal difficult. The hybrid usage of chaotic systems along with DNA and RNA sequencing improves the encryption efficiency of the algorithm and also makes it possible to decrypt the images at the same time without consuming too much of computation power.
This document proposes a new image encryption scheme based on chaotic encryption. It provides a fast encryption algorithm using a pseudorandom key stream generator based on coupled chaotic maps. Only the most important image components identified using discrete wavelet transform are encrypted. Statistical analysis shows the encrypted images have uniform histograms and negligible pixel correlations, resisting cryptanalysis attacks. The partial encryption also reduces computation time for applications with bandwidth and power constraints like mobile devices.
Hybrid chaotic map with L-shaped fractal Tromino for image encryption and dec...IJECEIAES
Insecure communication in digital image security and image storing are considered as important challenges. Moreover, the existing approaches face problems related to improper security at the time of image encryption and decryption. In this research work, a wavelet environment is obtained by transforming the cover image utilizing integer wavelet transform (IWT) and hybrid discrete cosine transform (DCT) to completely prevent false errors. Then the proposed hybrid chaotic map with L-shaped fractal Tromino offers better security to maintain image secrecy by means of encryption and decryption. The proposed work uses fractal encryption with the combination of L-shaped Tromino theorem for enhancement of information hiding. The regions of L-shaped fractal Tromino are sensitive to variations, thus are embedded in the watermark based on a visual watermarking technique known as reversible watermarking. The experimental results showed that the proposed method obtained peak signal-to-noise ratio (PSNR) value of 56.82dB which is comparatively higher than the existing methods that are, Beddington, Free, and Lawton (BFL) map with PSNR value of 8.10 dB, permutation substitution, and Boolean operation with PSNR value of 21.19 dB and deoxyribonucleic acid (DNA) level permutation-based logistic map with PSNR value of 21.27 dB.
A ROBUST CHAOTIC AND FAST WALSH TRANSFORM ENCRYPTION FOR GRAY SCALE BIOMEDICA...sipij
In this work, a new scheme of image encryption based on chaos and Fast Walsh Transform (FWT) has been proposed.
We used two chaotic logistic maps and combined chaotic encryption methods to the two-dimensional FWT of images.
The encryption process involves two steps: firstly, chaotic sequences generated by the chaotic logistic maps are used to
permute and mask the intermediate results or array of FWT, the next step consist in changing the chaotic sequences or
the initial conditions of chaotic logistic maps among two intermediate results of the same row or column. Changing the
encryption key several times on the same row or column makes the cipher more robust against any attack. We tested
our algorithms on many biomedical images. We also used images from data bases to compare our algorithm to those
in literature. It comes out from statistical analysis and key sensitivity tests that our proposed image encryption schemeprovides an efficient and secure way for real-time encryption and transmission biomedical images.
With the development of information security, the traditional image encryption methods have become
outdated. Because of amply using images in the transmission process, it is important to protect the confidential image
data from unauthorized access. This paper presents a new chaos based image encryption algorithm, which can improve
the security during transmission more effectively utilizes the chaotic systems properties, such as pseudo-random
appearance and sensitivity to initial conditions. Based on chaotic theory and decomposition and recombination of pixel
values, this new image scrambling algorithm is able to change the position of pixel, simultaneously scrambling both
position and pixel values. Experimental results show that the new algorithm improves the image security effectively to
avoid unscramble, and it also can restore the image as same as the original one, which reaches to the purposes of image
safe and reliable transmission.
Ieee a secure algorithm for image based information hiding with one-dimension...Akash Rawat
ieee a secure algorithm for image based information hiding with one-dimensional chaotic systems.It used 1 dimensional chaotic system.ieee paper related for image encryption
A novel secure image steganography method based on chaos theory in spatial do...ijsptm
This paper presents a novel approach of building a secure data hiding technique in digital images. The
image steganography technique takes the advantage of limited power of human visual system (HVS). It uses
image as cover media for embedding secret message. The most important requirement for a steganographic
algorithm is to be imperceptible while maximizing the size of the payload. In this paper a method is
proposed to encrypt the secret bits of the message based on chaos theory before embedding into the cover
image. A 3-3-2 LSB insertion method has been used for image steganography. Experimental results show a
substantial improvement in the Peak Signal to Noise Ratio (PSNR) and Image Fidelity (IF) value of the
proposed technique over the base technique of 3-3-2 LSB insertion.
A New Chaos Based Image Encryption and Decryption using a Hash FunctionIRJET Journal
This document proposes a new chaos-based image encryption and decryption scheme using Arnold's cat map for pixel permutation and the Lorenz system for diffusion. A hash function, specifically MurmurHash3, is used to generate the permutation and diffusion keys. This helps accelerate the diffusion process and reduces the number of cipher cycles needed compared to previous schemes. The encryption process involves first permuting the pixel positions using the cat map, with control parameters determined by the hash value of the original image. Then diffusion is performed using the Lorenz system to generate the keystream. Decryption follows the reverse process using the same keys. Security analysis demonstrates the scheme has a large key space and the encrypted images pass various statistical tests, indicating the
This document describes an image encryption and decryption technique using chaos algorithms. It uses the chaotic properties of the Henon map and Arnold cat map. The Henon map is used to generate pseudo-random key values for pixel shuffling. Pixel positions of the input image are first shuffled using the Arnold cat map. Then they are shuffled again using the sorted key values from the Henon map. This encrypts the image. Decryption reverses the process to recover the original pixel values and image. Experimental results show the encrypted image is secure and the original image can be recovered accurately using the correct key during decryption. The technique provides efficient and secure encryption of images for transmission.
New Chaotic Substation and Permutation Method for Image Encryptiontayseer Karam alshekly
New Chaotic Substation and Permutation Method for Image Encryption is introduced based on combination between Block Cipher and chaotic map. The new algorithm encrypts and decrypts a block of 500 byte. Each block is firstly permuted by using the hyper-chaotic map and then the result is substituted using 1D Bernoulli map. Finally the resulted block is XORed with the key block. The proposed cipher image subjected to number of tests which are the security analysis (key space analysis and key sensitivity analysis) and statistical attack analysis (histogram, correlation, and differential attack and information entropy) and all results show that the proposed encryption scheme is secure because of its large key space; it’s highly sensitivity to the cipher keys and plain-images.
Similar to A new block cipher for image encryption based on multi chaotic systems (20)
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
Design and simulation an optimal enhanced PI controller for congestion avoida...TELKOMNIKA JOURNAL
This document describes using a snake optimization algorithm to tune the gains of an enhanced proportional-integral controller for congestion avoidance in a TCP/AQM system. The controller aims to maintain a stable and desired queue size without noise or transmission problems. A linearized model of the TCP/AQM system is presented. An enhanced PI controller combining nonlinear gain and original PI gains is proposed. The snake optimization algorithm is then used to tune the parameters of the enhanced PI controller to achieve optimal system performance and response. Simulation results are discussed showing the proposed controller provides a stable and robust behavior for congestion control.
Improving the detection of intrusion in vehicular ad-hoc networks with modifi...TELKOMNIKA JOURNAL
Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.
Conceptual model of internet banking adoption with perceived risk and trust f...TELKOMNIKA JOURNAL
Understanding the primary factors of internet banking (IB) acceptance is critical for both banks and users; nevertheless, our knowledge of the role of users’ perceived risk and trust in IB adoption is limited. As a result, we develop a conceptual model by incorporating perceived risk and trust into the technology acceptance model (TAM) theory toward the IB. The proper research emphasized that the most essential component in explaining IB adoption behavior is behavioral intention to use IB adoption. TAM is helpful for figuring out how elements that affect IB adoption are connected to one another. According to previous literature on IB and the use of such technology in Iraq, one has to choose a theoretical foundation that may justify the acceptance of IB from the customer’s perspective. The conceptual model was therefore constructed using the TAM as a foundation. Furthermore, perceived risk and trust were added to the TAM dimensions as external factors. The key objective of this work was to extend the TAM to construct a conceptual model for IB adoption and to get sufficient theoretical support from the existing literature for the essential elements and their relationships in order to unearth new insights about factors responsible for IB adoption.
Efficient combined fuzzy logic and LMS algorithm for smart antennaTELKOMNIKA JOURNAL
The smart antennas are broadly used in wireless communication. The least mean square (LMS) algorithm is a procedure that is concerned in controlling the smart antenna pattern to accommodate specified requirements such as steering the beam toward the desired signal, in addition to placing the deep nulls in the direction of unwanted signals. The conventional LMS (C-LMS) has some drawbacks like slow convergence speed besides high steady state fluctuation error. To overcome these shortcomings, the present paper adopts an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to adjust its step size. Computer simulation outcomes illustrate that the given model has fast convergence rate as well as low mean square error steady state.
Design and implementation of a LoRa-based system for warning of forest fireTELKOMNIKA JOURNAL
This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos.The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.
Wavelet-based sensing technique in cognitive radio networkTELKOMNIKA JOURNAL
Cognitive radio is a smart radio that can change its transmitter parameter based on interaction with the environment in which it operates. The demand for frequency spectrum is growing due to a big data issue as many Internet of Things (IoT) devices are in the network. Based on previous research, most frequency spectrum was used, but some spectrums were not used, called spectrum hole. Energy detection is one of the spectrum sensing methods that has been frequently used since it is easy to use and does not require license users to have any prior signal understanding. But this technique is incapable of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the wavelet-based sensing is proposed to overcome this issue and detect spectrum holes. The main objective of this work is to evaluate the performance of wavelet-based sensing and compare it with the energy detection technique. The findings show that the percentage of detection in wavelet-based sensing is 83% higher than energy detection performance. This result indicates that the wavelet-based sensing has higher precision in detection and the interference towards primary user can be decreased.
A novel compact dual-band bandstop filter with enhanced rejection bandsTELKOMNIKA JOURNAL
In this paper, we present the design of a new wide dual-band bandstop filter (DBBSF) using nonuniform transmission lines. The method used to design this filter is to replace conventional uniform transmission lines with nonuniform lines governed by a truncated Fourier series. Based on how impedances are profiled in the proposed DBBSF structure, the fractional bandwidths of the two 10 dB-down rejection bands are widened to 39.72% and 52.63%, respectively, and the physical size has been reduced compared to that of the filter with the uniform transmission lines. The results of the electromagnetic (EM) simulation support the obtained analytical response and show an improved frequency behavior.
Deep learning approach to DDoS attack with imbalanced data at the application...TELKOMNIKA JOURNAL
A distributed denial of service (DDoS) attack is where one or more computers attack or target a server computer, by flooding internet traffic to the server. As a result, the server cannot be accessed by legitimate users. A result of this attack causes enormous losses for a company because it can reduce the level of user trust, and reduce the company’s reputation to lose customers due to downtime. One of the services at the application layer that can be accessed by users is a web-based lightweight directory access protocol (LDAP) service that can provide safe and easy services to access directory applications. We used a deep learning approach to detect DDoS attacks on the CICDDoS 2019 dataset on a complex computer network at the application layer to get fast and accurate results for dealing with unbalanced data. Based on the results obtained, it is observed that DDoS attack detection using a deep learning approach on imbalanced data performs better when implemented using synthetic minority oversampling technique (SMOTE) method for binary classes. On the other hand, the proposed deep learning approach performs better for detecting DDoS attacks in multiclass when implemented using the adaptive synthetic (ADASYN) method.
The appearance of uncertainties and disturbances often effects the characteristics of either linear or nonlinear systems. Plus, the stabilization process may be deteriorated thus incurring a catastrophic effect to the system performance. As such, this manuscript addresses the concept of matching condition for the systems that are suffering from miss-match uncertainties and exogeneous disturbances. The perturbation towards the system at hand is assumed to be known and unbounded. To reach this outcome, uncertainties and their classifications are reviewed thoroughly. The structural matching condition is proposed and tabulated in the proposition 1. Two types of mathematical expressions are presented to distinguish the system with matched uncertainty and the system with miss-matched uncertainty. Lastly, two-dimensional numerical expressions are provided to practice the proposed proposition. The outcome shows that matching condition has the ability to change the system to a design-friendly model for asymptotic stabilization.
Implementation of FinFET technology based low power 4×4 Wallace tree multipli...TELKOMNIKA JOURNAL
Many systems, including digital signal processors, finite impulse response (FIR) filters, application-specific integrated circuits, and microprocessors, use multipliers. The demand for low power multipliers is gradually rising day by day in the current technological trend. In this study, we describe a 4×4 Wallace multiplier based on a carry select adder (CSA) that uses less power and has a better power delay product than existing multipliers. HSPICE tool at 16 nm technology is used to simulate the results. In comparison to the traditional CSA-based multiplier, which has a power consumption of 1.7 µW and power delay product (PDP) of 57.3 fJ, the results demonstrate that the Wallace multiplier design employing CSA with first zero finding logic (FZF) logic has the lowest power consumption of 1.4 µW and PDP of 27.5 fJ.
Evaluation of the weighted-overlap add model with massive MIMO in a 5G systemTELKOMNIKA JOURNAL
The flaw in 5G orthogonal frequency division multiplexing (OFDM) becomes apparent in high-speed situations. Because the doppler effect causes frequency shifts, the orthogonality of OFDM subcarriers is broken, lowering both their bit error rate (BER) and throughput output. As part of this research, we use a novel design that combines massive multiple input multiple output (MIMO) and weighted overlap and add (WOLA) to improve the performance of 5G systems. To determine which design is superior, throughput and BER are calculated for both the proposed design and OFDM. The results of the improved system show a massive improvement in performance ver the conventional system and significant improvements with massive MIMO, including the best throughput and BER. When compared to conventional systems, the improved system has a throughput that is around 22% higher and the best performance in terms of BER, but it still has around 25% less error than OFDM.
Reflector antenna design in different frequencies using frequency selective s...TELKOMNIKA JOURNAL
In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Reagentless iron detection in water based on unclad fiber optical sensorTELKOMNIKA JOURNAL
A simple and low-cost fiber based optical sensor for iron detection is demonstrated in this paper. The sensor head consist of an unclad optical fiber with the unclad length of 1 cm and it has a straight structure. Results obtained shows a linear relationship between the output light intensity and iron concentration, illustrating the functionality of this iron optical sensor. Based on the experimental results, the sensitivity and linearity are achieved at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With the same wavelength, other performance parameters are also studied. Resolution and limit of detection (LOD) are found to be 0.3049 ppm and 0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not require any reagent for detection, enabling it to be simpler and cost-effective in the implementation of the iron sensing.
Impact of CuS counter electrode calcination temperature on quantum dot sensit...TELKOMNIKA JOURNAL
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
A progressive learning for structural tolerance online sequential extreme lea...TELKOMNIKA JOURNAL
This article discusses the progressive learning for structural tolerance online sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save robust accuracy while updating the new data and the new class data on the online training situation. The robustness accuracy arises from using the householder block exact QR decomposition recursive least squares (HBQRD-RLS) of the PSTOS-ELM. This method is suitable for applications that have data streaming and often have new class data. Our experiment compares the PSTOS-ELM accuracy and accuracy robustness while data is updating with the batch-extreme learning machine (ELM) and structural tolerance online sequential extreme learning machine (STOS-ELM) that both must retrain the data in a new class data case. The experimental results show that PSTOS-ELM has accuracy and robustness comparable to ELM and STOS-ELM while also can update new class data immediately.
Electroencephalography-based brain-computer interface using neural networksTELKOMNIKA JOURNAL
This study aimed to develop a brain-computer interface that can control an electric wheelchair using electroencephalography (EEG) signals. First, we used the Mind Wave Mobile 2 device to capture raw EEG signals from the surface of the scalp. The signals were transformed into the frequency domain using fast Fourier transform (FFT) and filtered to monitor changes in attention and relaxation. Next, we performed time and frequency domain analyses to identify features for five eye gestures: opened, closed, blink per second, double blink, and lookup. The base state was the opened-eyes gesture, and we compared the features of the remaining four action gestures to the base state to identify potential gestures. We then built a multilayer neural network to classify these features into five signals that control the wheelchair’s movement. Finally, we designed an experimental wheelchair system to test the effectiveness of the proposed approach. The results demonstrate that the EEG classification was highly accurate and computationally efficient. Moreover, the average performance of the brain-controlled wheelchair system was over 75% across different individuals, which suggests the feasibility of this approach.
Adaptive segmentation algorithm based on level set model in medical imagingTELKOMNIKA JOURNAL
For image segmentation, level set models are frequently employed. It offer best solution to overcome the main limitations of deformable parametric models. However, the challenge when applying those models in medical images stills deal with removing blurs in image edges which directly affects the edge indicator function, leads to not adaptively segmenting images and causes a wrong analysis of pathologies wich prevents to conclude a correct diagnosis. To overcome such issues, an effective process is suggested by simultaneously modelling and solving systems’ two-dimensional partial differential equations (PDE). The first PDE equation allows restoration using Euler’s equation similar to an anisotropic smoothing based on a regularized Perona and Malik filter that eliminates noise while preserving edge information in accordance with detected contours in the second equation that segments the image based on the first equation solutions. This approach allows developing a new algorithm which overcome the studied model drawbacks. Results of the proposed method give clear segments that can be applied to any application. Experiments on many medical images in particular blurry images with high information losses, demonstrate that the developed approach produces superior segmentation results in terms of quantity and quality compared to other models already presented in previeous works.
Automatic channel selection using shuffled frog leaping algorithm for EEG bas...TELKOMNIKA JOURNAL
Drug addiction is a complex neurobiological disorder that necessitates comprehensive treatment of both the body and mind. It is categorized as a brain disorder due to its impact on the brain. Various methods such as electroencephalography (EEG), functional magnetic resonance imaging (FMRI), and magnetoencephalography (MEG) can capture brain activities and structures. EEG signals provide valuable insights into neurological disorders, including drug addiction. Accurate classification of drug addiction from EEG signals relies on appropriate features and channel selection. Choosing the right EEG channels is essential to reduce computational costs and mitigate the risk of overfitting associated with using all available channels. To address the challenge of optimal channel selection in addiction detection from EEG signals, this work employs the shuffled frog leaping algorithm (SFLA). SFLA facilitates the selection of appropriate channels, leading to improved accuracy. Wavelet features extracted from the selected input channel signals are then analyzed using various machine learning classifiers to detect addiction. Experimental results indicate that after selecting features from the appropriate channels, classification accuracy significantly increased across all classifiers. Particularly, the multi-layer perceptron (MLP) classifier combined with SFLA demonstrated a remarkable accuracy improvement of 15.78% while reducing time complexity.
Levelised Cost of Hydrogen (LCOH) Calculator ManualMassimo Talia
The aim of this manual is to explain the
methodology behind the Levelized Cost of
Hydrogen (LCOH) calculator. Moreover, this
manual also demonstrates how the calculator
can be used for estimating the expenses associated with hydrogen production in Europe
using low-temperature electrolysis considering different sources of electricity
This study Examines the Effectiveness of Talent Procurement through the Imple...DharmaBanothu
In the world with high technology and fast
forward mindset recruiters are walking/showing interest
towards E-Recruitment. Present most of the HRs of
many companies are choosing E-Recruitment as the best
choice for recruitment. E-Recruitment is being done
through many online platforms like Linkedin, Naukri,
Instagram , Facebook etc. Now with high technology E-
Recruitment has gone through next level by using
Artificial Intelligence too.
Key Words : Talent Management, Talent Acquisition , E-
Recruitment , Artificial Intelligence Introduction
Effectiveness of Talent Acquisition through E-
Recruitment in this topic we will discuss about 4important
and interlinked topics which are
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...PriyankaKilaniya
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
Road construction is not as easy as it seems to be, it includes various steps and it starts with its designing and
structure including the traffic volume consideration. Then base layer is done by bulldozers and levelers and after
base surface coating has to be done. For giving road a smooth surface with flexibility, Asphalt concrete is used.
Asphalt requires an aggregate sub base material layer, and then a base layer to be put into first place. Asphalt road
construction is formulated to support the heavy traffic load and climatic conditions. It is 100% recyclable and
saving non renewable natural resources.
With the advancement of technology, Asphalt technology gives assurance about the good drainage system and with
skid resistance it can be used where safety is necessary such as outsidethe schools.
The largest use of Asphalt is for making asphalt concrete for road surfaces. It is widely used in airports around the
world due to the sturdiness and ability to be repaired quickly, it is widely used for runways dedicated to aircraft
landing and taking off. Asphalt is normally stored and transported at 150’C or 300’F temperature
Accident detection system project report.pdfKamal Acharya
The Rapid growth of technology and infrastructure has made our lives easier. The
advent of technology has also increased the traffic hazards and the road accidents take place
frequently which causes huge loss of life and property because of the poor emergency facilities.
Many lives could have been saved if emergency service could get accident information and
reach in time. Our project will provide an optimum solution to this draw back. A piezo electric
sensor can be used as a crash or rollover detector of the vehicle during and after a crash. With
signals from a piezo electric sensor, a severe accident can be recognized. According to this
project when a vehicle meets with an accident immediately piezo electric sensor will detect the
signal or if a car rolls over. Then with the help of GSM module and GPS module, the location
will be sent to the emergency contact. Then after conforming the location necessary action will
be taken. If the person meets with a small accident or if there is no serious threat to anyone’s
life, then the alert message can be terminated by the driver by a switch provided in order to
avoid wasting the valuable time of the medical rescue team.
Supermarket Management System Project Report.pdfKamal Acharya
Supermarket management is a stand-alone J2EE using Eclipse Juno program.
This project contains all the necessary required information about maintaining
the supermarket billing system.
The core idea of this project to minimize the paper work and centralize the
data. Here all the communication is taken in secure manner. That is, in this
application the information will be stored in client itself. For further security the
data base is stored in the back-end oracle and so no intruders can access it.
Blood finder application project report (1).pdfKamal Acharya
Blood Finder is an emergency time app where a user can search for the blood banks as
well as the registered blood donors around Mumbai. This application also provide an
opportunity for the user of this application to become a registered donor for this user have
to enroll for the donor request from the application itself. If the admin wish to make user
a registered donor, with some of the formalities with the organization it can be done.
Specialization of this application is that the user will not have to register on sign-in for
searching the blood banks and blood donors it can be just done by installing the
application to the mobile.
The purpose of making this application is to save the user’s time for searching blood of
needed blood group during the time of the emergency.
This is an android application developed in Java and XML with the connectivity of
SQLite database. This application will provide most of basic functionality required for an
emergency time application. All the details of Blood banks and Blood donors are stored
in the database i.e. SQLite.
This application allowed the user to get all the information regarding blood banks and
blood donors such as Name, Number, Address, Blood Group, rather than searching it on
the different websites and wasting the precious time. This application is effective and
user friendly.
Generative AI Use cases applications solutions and implementation.pdfmahaffeycheryld
Generative AI solutions encompass a range of capabilities from content creation to complex problem-solving across industries. Implementing generative AI involves identifying specific business needs, developing tailored AI models using techniques like GANs and VAEs, and integrating these models into existing workflows. Data quality and continuous model refinement are crucial for effective implementation. Businesses must also consider ethical implications and ensure transparency in AI decision-making. Generative AI's implementation aims to enhance efficiency, creativity, and innovation by leveraging autonomous generation and sophisticated learning algorithms to meet diverse business challenges.
https://www.leewayhertz.com/generative-ai-use-cases-and-applications/
Impartiality as per ISO /IEC 17025:2017 StandardMuhammadJazib15
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DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELijaia
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
A new block cipher for image encryption based on multi chaotic systems
1. TELKOMNIKA Telecommunication, Computing, Electronics and Control
Vol. 18, No. 6, December 2020, pp. 2983~2991
ISSN: 1693-6930, accredited First Grade by Kemenristekdikti, Decree No: 21/E/KPT/2018
DOI: 10.12928/TELKOMNIKA.v18i6.13746 2983
Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA
A new block cipher for image encryption based on multi
chaotic systems
Donia Fadhil Chalob, Amal Abdulbaqi Maryoosh, Zainab Mohammed Essa, Elaf Nassir Abbud
Department of computer Science, Collage of education, Mustansiyiah University, Iraq
Article Info ABSTRACT
Article history:
Received Jul 28, 2019
Revised Mar 5, 2020
Accepted Jun 12, 2020
In this paper, a new algorithm for image encryption is proposed based on three
chaotic systems which are Chen system, logistic map and two-dimensional
(2D) Arnold cat map. First, a permutation scheme is applied to the image, and
then shuffled image is partitioned into blocks of pixels. For each block, Chen
system is employed for confusion and then logistic map is employed for
generating subsititution-box (S-box) to substitute image blocks. The S-box is
dynamic, where it is shuffled for each image block using permutation
operation. Then, 2D Arnold cat map is used for providing diffusion, after that
XORing the result using Chen system to obtain the encrypted image. The high
security of proposed algorithm is experimented using histograms, unified
average changing intensity (UACI), number of pixels change rate (NPCR),
entropy, correlation and key space analyses.
Keywords:
Arnold cat map
Chaotic
Chen system
Image encryption
Logistic map This is an open access article under the CC BY-SA license.
Corresponding Author:
Amal Abdulbaqi Maryoosh,
Department of computer Science, Collage of education,
Mustansiyiah University,
Baghdad, Iraq.
Email: amalmaryoosh@uomustansiriyah.edu.iq
1. INTRODUCTION
With the fast progress of image transmission through computer networks, particularly the Internet,
images security has turned into a main issue. Image encryption, specifically, is critically required yet it is a
challenging task—it is totally not the same as text encryption due to some the inherent features of an image,
for example, tremendous data bulk and highly redundant, they are for the most part difficult to deal with by
utilizing traditional algorithms [1]. To achieve a secure encryption method, two basic characteristics must be
followed. The first is the confusion feature which necessitates that, encrypted text should has arbitrary
appearance, which means that the pixel values uniformly distributed. The second is the diffusion feature that
should create totally unlike encrypted text by similar keys for the equivalent original text. The secure
transmission of color images through public channel, chaotic systems that fulfill the main prerequisites of
confusion and diffusion are distinguished based on their reactive to control parameters and initial conditions,
pseudorandomness and ergodicity. Exploiting these favorable features, chaos-based algorithms have revealed
superior characteristics in complexity and security [2, 3].
Several studies are related to this work, Z. l. Zhu et al. [4] suggested an image encryption algotithm
utilizing logistic map for diffusion and Arnold cat map for bit- level permutation. M. J. Rostami et al. [5]
employed logistic map for the encryption of gray-scale image, divides the image into blocks and encrypts them
with XOR operation and chaotic windows. W. Zhang et al. [6] a three-dimensional bit matrix permutation is
proposed, via gathering features of Chen system with a three-dimensional cat map in permutation operation, a
double random place bit-level permutation in three-dimensional (3D) matrix is developed. Liu and Miao [7]
2. ISSN: 1693-6930
TELKOMNIKA Telecommun Comput El Control, Vol. 18, No. 6, December 2020: 2983 - 2991
2984
proposed a new image encryption algorithm based on parameter-varied logistic chaotic map to shuffle the plain
image and dynamical algorithm to encrypt the image. L. Xu et al. [8] presents a new bit-level algorithm of
image encryption that depends on piecewise linear chaotic maps (PWLCM), diffuse the image sequences via
a new diffusion strategy.
Then, the control of a chaotic map is utilized for swapped the binary elements in the sequences, which
permute bits in particular bitplane into another bitplane. X. Wang et al. [9] suggests a method for block image
encryption depended on hybrid chaotic maps and dynamic random growth technique. In diffusion operation,
an intermediary parameter is determined by the image block. The intermediary parameter is utilized as
the initial parameter of chaotic cat map in order to generate a random key stream. Suryadi M. T. et al. [10]
built a chaotic encryption scheme for digital image by utilizing logistic map for key stream as a random number
generator. Xiuli Chai et al. [11] introduced a scheme for image encryption depended on the memristive chaotic
system, compressive sensing and elementary cellular automata. Wavelet coefficients of an original image are
permuted using the zigzag path and elementary cellular automata. After that, the compressive sensing is utilized
to compress and encrypt the permuted image. Hash value of SHA 512 of plain image is used to gain some
parameters utilized in encryption operation. Hongyao Deng et al. [12] proposed a chaos-based image
encryption algorithm, by shuffle to mask original organization of the pixels in images using cat map and
diffusion to mask their values using logistic map. Salah T. Allawi [13] presented a new method to encrypt RGB
image by dividing the image into two equal parts, encrypting each part using a secret key generated by
one-dimensional (1D) logistic mapping and permutation the pixels position using random numbers generated
by using linear-feedback shift registers (LFSRs). Pan et al. [14] studied the digital image encryption technology
with the dual logistic chaotic map as a tool. Ye, G., & Huang [15] presented a chaotic image encryption
algorithm by using SHA-3 hash function, cat map, logistic map and auto-updating system. At the same time,
for various rounds of iteration and various images, the algorithm demonstrates like one-time pad. Ye, G. et al.
[16] presented method includes permutation, modulation and diffusion processes. This technique overcomes
the drawback in traditional methods of strictly permuting the places of pixels before diffusion. Information
entropy is utilized to effect the keystream generation. Zhang Y. [17] suggested a plaintext-related image
encryption algorithm depended on hyper chaotic Lorenz system, six pseudorandom matrices are generated
using the hyper chaotic Lorenz system, such that, two of the matrices utilize add-modulus operations to diffuse
the plaintext unrelated image, other four matrices confuse the plaintext related image. N. Oussama et al. [18]
designed a novel symmetric image encryption method based on polar decomposition of matrices and 1D
logistic map.
In this paper, a new block algorithm for color image encryption is suggested based on three chaotic
systems to overcome the problem of high computation, pattern appearance issue and so slow when using
traditional algorithms image encryption. High confusion is provided by chaotic system and dynamic S-box and
high diffusion is provided by permutation methods to increase the security and efficiency of image encryption.
This paper results are experimented by information entropy, correlation, histogram, NPCR, UACI and key
space. The experimental results show that the proposed scheme efficient and more secure for image encryption.
The rest of this paper is organized as follows. In section 2, the methods that used in the proposed algorithm are
introduced. The suggested scheme in details is presented in section 3. Then, security experiments with
comparison are achieved in section 4 to show the effectiveness of our scheme. Finally, some conclusions that
extracted from this work are in section 5.
2. CHAOTIC SYSTEMS
The proposed algorithm employs three chaotic maps in this paper, namely Chen system [19],
one-dimensional (1D) logistic map [20] and two-dimensional (2D) Arnold cat map [21].
2.1. Chen system
Chen chaotic system [19] is expressed by in (1):
{
ẋ = a(y − x)
ẏ = (c − a)x − xz + cy
ż = xy − bz
(1)
where a = 35, b = 3 and c = 28 are parameters, x, y, z are state variables. The attractor and phase diagram of
Chen system are illustrated in Figures 1 (a) and (b), respectively.
3. TELKOMNIKA Telecommun Comput El Control
A new block cipher for image encryption based on multi chaotic systems (Donia Fadhil Chalob)
2985
2.2. Logistic map
In 1845, Pierre Verhulst suggested logistic map, that's a simple and popular chaotic map. When used
in 1979 via the biologist Robert M. May, logistic map became very common. Where the equation of one
dimensional logistic map is shown in (2):
xn+1 = μ xn (1 − xn) (2)
In which xn∊[0,1], x0 denotes the initial condition and μ is a constant parameter between 0 and 4. For
(3.5699 < μ ≤ 4), in (2) shows a chaotic behavior [20]. By reason of its simplicity and high efficiency, this
paper employed the chaotic systems times in its algorithm.
Figure 1. Chaotic attractor; (a) Chen attractor 3-D, (b) phase diagram (x-y)
2.3. Arnold cat map
The classic Arnold cat map is an invertible chaotic map of two dimensions [21] described via in (3):
[
xn+1
yn+1
] = [
1 1
1 2
] [
xn
yn
] mod 1 (3)
where xn, yn are the position in the matrix of samples (N×N), n=1,2,3,…, N-1 and xn+1, yn+1 are the position
transformed after cat map. The map is recognized to become chaotic, by explanation of geometry displayed in
Figure 2, where one can notice that a square unit is at the beginning stretched by means of linear transformation
and then folded through mod, modulo operation.
Figure 2. Geometric explanation of 2D cat map
3. PROPOSED ALGORITHM
The encryption algorithm contains three main operations, which are: permutation, substitution and
add chaotic keys. At first, the plain image will be input to permutation step and then the permuted image will
be divided into 4x4 blocks to be entered to n iterations of add Chen key, then substitution which is done by
generating dynamic S-box using logistic map. After the end of iterations the resulting image will be permuted
using Arnold cat map to increase the diffusion. Finally, XORed the resulted image with Chen key which
provide extra confusion process. The general structure diagram of suggested algorithm shown in Figure 3.
4. ISSN: 1693-6930
TELKOMNIKA Telecommun Comput El Control, Vol. 18, No. 6, December 2020: 2983 - 2991
2986
Figure 3. General structure of proposed algorithm
3.1. Permutation method
In order to achieve the permutation technique of cryptosystems, scrambleness behavior is required.
In this algorithm, two permutation methods are used for providing a high level of diffusion. In this method we
relied on scrambling rows and columns based on sum invariance of row and column through circular shift
process. In the beginning we shifts each row in image by the total sum of the row and column's pixel values
and save the result image in a variable, and then transpose the resulting image and implement the same method
in each column on the transposed image. Table 1 shown the random swap of 10x10 ladybug sub image pixels.
Figure 4 shown the plain ladybug image and the resulting image after permutation.
Table 1. Original pixel location on left and their new position on right
The random swap of 10x10 ladybug sub image pixels
86 85 80 81 73 76 77 121 126 33
99 98 98 97 93 89 125 164 151 103
120 124 113 118 99 125 175 204 192 177
126 117 123 108 132 179 215 212 200 184
121 117 123 121 181 222 231 222 203 168
112 122 91 167 223 245 240 225 180 172
104 75 94 202 252 255 240 193 165 208
102 27 165 239 252 254 214 162 197 239
45 97 213 249 254 240 162 191 251 217
12 179 247 255 245 187 169 241 243 206
97 45 254 125 187 121 89 121 98 222
99 75 77 191 175 200 231 124 255 197
245 123 162 151 241 103 164 80 73 172
162 118 126 206 192 120 203 249 179 104
225 132 217 86 33 85 177 245 240 117
251 255 12 97 99 213 126 125 212 113
208 169 27 94 179 202 98 240 165 81
102 193 91 121 165 252 247 204 168 93
122 243 108 223 167 76 239 180 112 222
123 239 181 240 252 215 254 184 117 214
(a) (b)
Figure 4. (a) Plain ladybug image, (b) permuted ladybug image
5. TELKOMNIKA Telecommun Comput El Control
A new block cipher for image encryption based on multi chaotic systems (Donia Fadhil Chalob)
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3.1.1. Permutation algorithm
Input: plain image (m)
Output: permuted image (p1)
Step1: read plain image(m)
Step2: for col1 ←1: size (m)
I1← circular_shift (sum (m (column)))
end
Step3: for row1←1: size (m)
I2← circular_shift (sum (m (row)))
end
Step4: transpose(I2)
Step5: for col2 ←1: size (m)
I3← circular_shift (sum (m (column)))
end
Step6: for row2←1: size (m)
I4← circular_shift (sum (m (row)))
end
Step7: p1← I4
3.2. Substitution
In this process, this paper generates a dynamic S-box using logistic map and improve the key
sensitivity by implementing the proposed permutation method on the S-box in each round, where each block
will be substituted with a new S-box, this operation will provide one time pad property. Figure 5 demonstrates
the result of encryption house image by using dynamic S-box only.
(a) (b)
Figure 5. (a) Plain house image, (b) image after substitution process
3.3. Encryption algorithm
Input: permuted image (p1), Chen_key, Logistic parameters(x,n,r0) block size(z)
Output: encrypted image (c)
Step1: read permuted image (p1)
Step2: k1 ← XOR(p1, Chen_key)
Step3: Sbox ←Logistic_map(x,n,r0)
for j ← 1:z
sub_byte← permutation (Sbox)
s← sub_byte (p)
end
Step4: p2 ← Aronld cat_map(s)
Step5: k2 ← xor (Chen_key, p2)
Step6: c ← k2
3.4. Decryption algorithm
Input: encrypted image (c), Chen_key, Inv_Logistic parameters(x1,n1,r0) block size(z)
Output: plain image (m)
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Step1: read encrypted image (c)
Step2: k2 ← xor (Chen_key, c)
Step3: p2 ← Aronld cat_map(k2)
Step4: Inv_ Sbox ← Inv_Logistic_map(x1,n1,r0)
for j ← 1:z
Inv_ sub_byte← Inv_ permutation (Inv_Sbox)
s← Inv_sub_byte (p2)
end
Step5: k1 ← XOR(s, Chen_key)
Step6: m ← k1
4. SECURITY ANALYSIS
The results of series of tests are reviewed in this section to illustrate the effectiveness of the suggested
algorithm. The valuation is made up of various practical experiments. At the end of this section, a comparison
is made between the proposed algorithm and in [17]. The experiments are performed via Matlab R2013a on a
computer with Intel Core i3 CPU 2.10 GHz, 3 GB of RAM.
4.1. Histogram analysis
Histogram analysis is used to explain the confusion and diffusion characteristic of the encryption
algorithm. Figure 6 shown the difference in image distribution among plain flower image, its permutation and
encryption.
(a) (b) (c)
(d) (e) (f)
(g) (h) (i)
Figure 6. Histogram analysis; (a), (b) and (c) histogram plain flower image of RGB, (e) and (f) are histogram
permuted image of RGB, (g), (h) and (i) are histogram encrypted image of RGB
4.2. Correlation coefficients analysis
Every pixel is extremely associated with its neighboring pixels in the image data [22]. A typical
encryption algorithm should output cipher image in the neighboring pixels without such a correlation. In
horizontal, diagonal and vertical orientations, the correlation between two neighboring pixels is studied by
following equations:
7. TELKOMNIKA Telecommun Comput El Control
A new block cipher for image encryption based on multi chaotic systems (Donia Fadhil Chalob)
2989
rxy =
cov(x,y)
√D(x)√D(y)
, (4)
D(x) =
1
N
∑ (xj −
1
N
∑ xj
N
j=1 )2N
J=1 , (5)
cov(x, y) =
1
N
∑ (xj −
1
N
∑ xj
N
j=1 )N
j=1 (yj −
1
N
∑ yj
N
j=1 ). (6)
x and y are two adjacent pixel intensity values in an image, N is the number of neighboring pixels chosen from
the image to determine the correlation. The results of correlation of various encrypted images are displayed in
Table 2.
Table 2. Correlation coefficients of two neighboring pixels in encrypted images of proposed algorithm
Images
Correlation of Proposed Algorithm
Vertical Horizontal Diagonal
House -0.0089 -0.0049 -0.0125
Flower -0.0041 -0.0038 0.0034
Pepper 0.0020 -0.0035 0.0016
Lion -0.0018 -0.0025 0.0026
Bird -0.0027 0.0028 0.0030
Garden -0.0020 0.0039 0.0033
Horse 0.0060 -0.0036 -3.1399e-04
Sky -0.0030 -0.0024 0.0021
Ladybug -0.0037 0.0074 -0.0021
Splash -0.0062 0.0020 -0.0036
4.3. Information entropy analysis
Information entropy evaluates uncertainty of a random variable as following [23]:
E = ∑ P(i) log (
1
P(i)
) ,256
i=1 (7)
where P(i) is the eventuality presence of pixel i. A larger entropy value denotes a bigger security level that used
to assess the images encryption. Commonly, an entropy value so close to the typical value of 8 is regarded
secure from a brute force attack. The values of information entropy that obtained from proposed algorithm are
closer to 8, this shows that the proposed method has good random. Table 3 shows the values of information
entropy for the various plain images and encrypted images.
Table 3. Information entropy of plain and encrypted image of proposed algorithm
Images Entropy of plain images Entropy of proposed system
House 7.7871 7.9990
Flower 7.7666 7.9991
Pepper 7.7124 7.9989
Lion 7.8794 7.9989
Bird 7.6741 7.9977
Garden 7.7955 7.9990
Horse 7.6143 7.9988
Sky 7.9339 7.9990
Ladybug 7.5706 7.9990
Splash 7.3795 7.9990
4.4. Analysis of resisting differential attacks
Differential attack studies how a minor changing in an original image is able to influence
corresponding encrypted image. A typical encryption algorithm have to be able to withstand differential attack,
which means, any tiny change (even if changed a bit) in an original image will lead in a totally different
encrypted image. Number of pixels change rate (NPCR) and unified average changing intensity (UACI),
described by in (8) and (9), are two of the most common indicators to determine the competence of differential
attacks resisting in encrypted image [24]:
NPCR =
1
W×H
∑ ∑ dij × 100%H
j=1 ,W
i=1 (8)
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UACI =
1
255 ×W×H
∑ ∑ |Cij
1
Cij
2
|H
j=1
W
i=1 × 100%, (9)
where H and W refer to the height and width of the encrypted images, C1
and C2
are two cipher images and dij
is defined by in (10):
dij = {
0, Cij
1
= Cij
2
,
1, Cij
1
≠ Cij
2
.
(10)
The typical value of NPCR and UACI are 99.61 and 33.46 [7]. This paper implemented NPCR and UACI
measures on ten color images and the two indicator results are close to the optimal value. Table 4 shown
the results of NPCR and UACI in proposed scheme.
Table 4. UACI and NPCR indicator of encrypted image of proposed algorithm
Images
Proposed Algorithm
UACI NPCR
House 32.09 99.58
Flower 33.74 99.64
Pepper 33.86 99.61
Lion 33.57 99.61
Bird 33.92 99.61
Garden 33.41 99.61
Horse 33.41 99.61
Sky 33.80 99.60
Ladybug 34.07 99.61
Splash 33.58 99.62
4.5. Key space analysis
The encryption algorithm contains the keys: 1) initial values of x, y, z and x0 ; 2) control parameter
of a, b, c and μ. In general, the valid precision of the initial conditions could be set to 10-14
for continuous
chaotic system exhibited as nonlinear differential equation. Thus, the size of key space could reach 2112
> 2100
[25]. Thus, it is noticed that the value of the chaos system key space is much larger and the proposed algorithm
can highly resist against brute-force attacks. Table 5 demonstrates the results of Pepper image encrypted using
proposed algorithm and in [17].
Table 5. Comparison results of proposed algorithm with [17]
Test Proposed Algorithm [17]
Correlation Coefficients V 0.0020
H -0.0035
D 0.0016
V 0.013633
H -0.003522
D 0.007701
Entropy 7.9989 7.9992
NPCR
UACI
99.61
33.86
99.60
33.48
5. CONCLUSION
In this paper, a new block image encryption algorithm has been introduced to provide high level of
security for color image encryption on the basis of the combination of permutation method, chaotic systems
and dynamic S-box. Whereas the random permutation and Arnold cat map scrambling provide high level of
diffusion, the substitution process provide high confusion using Chen system and improve the key sensitivity
by generating a one-time S-box using logistic map. Also, the use of chaotic system offer high randomness,
large key space, key sensitivity and confusion. The effectiveness of this algorithm has been confirmed through
above experiment results. According to these results, the proposed algorithm offers high resistance against
statistical and differential attacks.
ACKNOWLEDGEMENTS
We would like to thank Mustansiriyah university (www.uomustansiriyah.edu.iq), Baghdad, Iraq for
its support in the present work.
9. TELKOMNIKA Telecommun Comput El Control
A new block cipher for image encryption based on multi chaotic systems (Donia Fadhil Chalob)
2991
REFERENCES
[1] Y. Wang, K. W. Wong, X. Liao, and G. Chen, “A new chaos-based fast image encryption algorithm,” Applied Soft
Computing, vol. 11, no. 1, pp. 514-522, 2011.
[2] N. K. Pareek, V. Patidar, and K. K. Sud, “Diffusion–substitution based gray image encryption scheme,” Digital
Signal Processing, vol. 23, no. 3, pp. 894-901, 2013.
[3] I. Hussain, T. Shah, and M. A. Gondal, “Application of S -box and chaotic map for image encryption,” Mathematical
and Computer Modelling, vol. 57, no. 9-10, pp. 2576–2579, 2013.
[4] Z. Zhu, W. Zhang, K. Wong, and H. Yu, “A chaos-based symmetric image encryption scheme using a bit-level
permutation,” Information Sciences, vol. 181, no. 6, pp. 1171-1186, 2011.
[5] M. J. Rostami, A. Shahba, S. Saryazdi, and H. Nezamabadi-pour, “A novel parallel image encryption with chaotic
windows based on Logistic map,” Computers and Electrical Engineering, vol. 62, pp.3 84-400, 2017.
[6] W. Zhang, H. Yu, Y. Zhao, Z. Zhu, “Image encryption based on three-dimensional bit matrix permutation,” Signal
Processing, vol. 118, pp. 36-50, 2016.
[7] L. Liu, and S. Miao, “A new image encryption algorithm based on Logistic chaotic map with varying parameter,”
SpringerPlus, vol. 5, no. 1, 2016.
[8] L. Xu, Z. Li, J. Li, and W. Hua, “A novel bit-level image encryption algorithm based on chaotic maps”, Optics and
Lasers in Engineering, vol. 78, pp. 17-25, 2016.
[9] X. Wang, L. Liu, and Y. Zhang, “A novel chaotic block image encryption algorithm based on dynamic random
growth technique,” Optics and Lasers in Engineering, vol. 66, pp. 10-18, 2015.
[10] Suryadi M. T., E. Nurpeti, and D. Widya, “Performance of Chaos-Based Encryption Algorithm for Digital Image,”
TELKOMNIKA Telecommunication Computing Electronics and Control, vol. 12, no. 3, pp. 675-682, 2014.
[11] X. Chai, X. Zheng, Z. Gan, D. Han, and Y. Chen, “An image encryption algorithm based on chaotic system and
compressive sensing,” Signal Processing, vol. 148, pp. 124-144, 2018.
[12] Hongyao Deng, Qingxin Zhu, Xiuli Song and Jingsong Tao, “Chaos-Based Image Encryption Algorithm
Using Decomposition,” TELKOMNIKA Telecommunication Computing Electronics and Control, vol. 12, no. 1,
pp. 575-583, 2014.
[13] Salah T. Allawi, “Image Encryption Based on Chaotic Mapping and Random Numbers,” Journal of Engineering and
Applied Sciences, vol. 14, no. 19, pp. 6954-6958, 2019.
[14] H. Pan, Y. Lei, and C. Jian, “Research on digital image encryption algorithm based on double Logistic chaotic map,”
EURASIP Journal on Image and Video Processing, vol. 2018, no. 142, 2018.
[15] G. Ye, and X. Huang, “A secure image encryption algorithm based on chaotic maps and SHA-3,” Security and
Communication Networks, vol. 9, no. 13, pp. 2015-2023, 2016.
[16] G. Ye, C. Pan, X. Huang, Z. Zhao, and J. He, “A Chaotic Image Encryption Algorithm Based on Information
Entropy,” International Journal of Bifurcation and Chaos, vol. 28, no. 1, pp. 1-11, 2018.
[17] Y. Zhang, “A Chaotic System Based Image Encryption Algorithm using Plaintext-related Confusion,”
TELKOMNIKA Telecommunication Computing Electronics and Control, vol. 12, no. 11, pp. 7952-7962, 2014.
[18] N. Oussama, B. Assia, and N. Lemnouar, “Secure image encryption scheme based on polar decomposition and chaotic
map,” International Journal of Information and Communication Technology, vol. 10, no. 4, pp. 437-453, 2017.
[19] H. Dai, L. X. Jia, M. Hui, and G.-Q. Si, “A new three-dimensional chaotic system and its modifed generalized
projective synchronization,” Chin. Phys. B, vol. 20, no. 4, pp. 1-10, 2011.
[20] J. A. P. Artiles, D. P. B. Chaves and C. Pimentel, “Image encryption using block cipher and chaotic sequences,”
Signal Processing: Image Communication, vol. 79, pp. 24-31, 2019.
[21] G. Chen, Y. Mao, and C. K. Chui, “A symmetric image encryption scheme based on 3D chaotic cat maps,” Chaos,
Solitons and Fractals, vol. 21, no. 3, pp. 749-761, 2004.
[22] R. Sridevi, P. Philominathan, P. Praveenkumar, J. B. B. Rayappan, and R. Amirtharajan, “Logistic and Standard
Coupled Mapping on Pre and Post Shuffled Images: A Method of Image Encryption,” Asian J. Sci. Res, vol. 10,
no. 1, pp. 10-23, 2017.
[23] P. Ramasamy, V. Ranganathan, S. Kadry, R. Damaševičius, and T. Blažauskas, “An Image Encryption Scheme Based
on Block Scrambling, Modified Zigzag Transformation and Key Generation Using Enhanced Logistic—Tent Map,”
Entropy, vol. 21, no. 7, pp. 1-17, 2019.
[24] T. Li, J. Shi, X. Li, J. Wu, and F. Pan, “Image Encryption Based on Pixel-Level Diffusion with Dynamic Filtering
and DNA-Level Permutation with 3D Latin Cubes,” Entropy, vol. 21, no. 3, pp. 1-21, 2019.
[25] H. Liu, A. Kadir, and P. Gong, “A fast color image encryption scheme using one-time S-Boxes based on complex
chaotic system and random noise,” Optics Communications, vol. 338, pp. 340-347, 2015.