The document proposes and evaluates a new digital image security scheme that uses Residue Number System (RNS) encoding/decoding and a modified Arnold transform algorithm. Key points:
- The encryption process encodes the plain image into residual images using RNS, then encrypts them using the modified Arnold transform.
- The decryption process decrypts the cipher image using the inverse Arnold transform, then decodes the residual images back into the plain image using RNS and the Chinese Remainder Theorem.
- Experimental results on test images of different sizes and formats show the scheme can effectively encrypt and decrypt without information loss. Security analysis also indicates resistance to statistical attacks like histograms and strong sensitivity to encryption keys.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
The document discusses video compression using the Set Partitioning in Hierarchical Trees (SPIHT) algorithm and neural networks. It presents the principles of SPIHT coding and the backpropagation algorithm for neural networks. Various neural network training algorithms are tested for compressing video frames, including gradient descent with momentum and adaptive learning. The results show the compressed frames with different algorithms, and gradient descent with momentum and adaptive learning achieved the best compression ratio of 1.1737089:1 while maintaining image clarity.
A NEW ALGORITHM FOR DATA HIDING USING OPAP AND MULTIPLE KEYSEditor IJMTER
Steganography gained significance in the past few years due to the increasing need
for providing secrecy in an open environment like the internet. With almost anyone can
observe the communicated data all around, steganography attempts to hide the very existence
of the message and make communication undetectable. In this paper we propose a modern
technique with Integer Wavelet transform (IWT) and double key to accomplish high hiding
capability, high security and good visual quality. Here cover image is transformed in to
wavelet transform co-efficients and the coefficients are selected randomly by using Key-2 for
embedding the data. Key-1 is used to calculate the number of bits to be embedded in the
randomly selected coefficients. Finally the Optimum Pixel Adjustment Process(OPAP) is
applied to the stego image to reduce the data embedding error.
This document presents a technique for steganography using the least significant bit (LSB) and an encryption method. It discusses how the LSB technique works by replacing the LSB of pixels in a cover image with bits from a secret image. It then proposes encrypting the LSB plane of the encoded image by altering its columns at regular intervals before generating the stego image. This increases security by making it harder to extract the secret image through steganalysis while maintaining image quality. MATLAB code demonstrates embedding a secret image in a cover image using LSB, encrypting the LSB plane, generating the stego image, and successfully extracting the secret image.
A robust combination of dwt and chaotic function for image watermarkingijctet
This document summarizes a research paper on a robust image watermarking technique that combines discrete wavelet transform (DWT) and a chaotic function. The proposed method embeds a watermark into selected blocks of the low-frequency DWT subband of an image. It calculates the Euclidean distance between blocks of the watermark and image to select the most similar block for embedding. Experimental results on standard test images show the proposed method achieves better performance than previous methods in terms of PSNR and structural similarity under compression attacks. The extraction accuracy remains high even with noise attacks, though it degrades more under filtering attacks.
IRJET- LS Chaotic based Image Encryption System Via Permutation ModelsIRJET Journal
This document proposes an image encryption system using logistic sine map and permutation models. The system works as follows:
1. A plain image is converted to grayscale and decomposed into 8 bit planes.
2. Each bit plane is randomly scrambled.
3. A logistic sine map is used to generate a key to partially encrypt each bit plane.
4. The bits planes are then permuted to obtain the final encrypted image. Logistic sine maps are well-suited for this approach due to their sensitivity to initial parameter values and ability to generate seemingly random outputs. The system aims to increase security by efficiently scrambling and permuting the bit plane values of the input image.
The document presents a method for human action recognition using both RGB and depth data from an RGB-D sensor. Motion History Images (MHIs) are generated from RGB videos and Depth Motion Maps (DMMs) are generated from depth data after rotating the 3D point clouds. A 4-channel Deep Convolutional Neural Network is trained with one channel for MHIs and three channels for the rotated DMM views. Evaluated on the UTD-MHAD dataset, the proposed method achieves better recognition accuracy when fusing both RGB and depth modalities compared to using each individually.
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.
A secured data transmission system by reversible data hiding with scalable co...IAEME Publication
The document describes a method for secure image transmission that combines reversible data hiding, encryption, compression, and steganography. It involves three main steps:
1. Reversible data hiding is used to embed the original image data by reserving room before encryption. Some pixel least significant bit values are embedded in other pixels.
2. Scalable compression is then applied to further secure the image.
3. The compressed, encrypted image then has additional data hidden within it using steganography techniques for transmission.
The receiving end performs the inverse processes of extracting the data, decompressing the image, and recovering the original embedded image in a lossless and secure manner. The method aims to achieve high quality encrypted
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
The document discusses video compression using the Set Partitioning in Hierarchical Trees (SPIHT) algorithm and neural networks. It presents the principles of SPIHT coding and the backpropagation algorithm for neural networks. Various neural network training algorithms are tested for compressing video frames, including gradient descent with momentum and adaptive learning. The results show the compressed frames with different algorithms, and gradient descent with momentum and adaptive learning achieved the best compression ratio of 1.1737089:1 while maintaining image clarity.
A NEW ALGORITHM FOR DATA HIDING USING OPAP AND MULTIPLE KEYSEditor IJMTER
Steganography gained significance in the past few years due to the increasing need
for providing secrecy in an open environment like the internet. With almost anyone can
observe the communicated data all around, steganography attempts to hide the very existence
of the message and make communication undetectable. In this paper we propose a modern
technique with Integer Wavelet transform (IWT) and double key to accomplish high hiding
capability, high security and good visual quality. Here cover image is transformed in to
wavelet transform co-efficients and the coefficients are selected randomly by using Key-2 for
embedding the data. Key-1 is used to calculate the number of bits to be embedded in the
randomly selected coefficients. Finally the Optimum Pixel Adjustment Process(OPAP) is
applied to the stego image to reduce the data embedding error.
This document presents a technique for steganography using the least significant bit (LSB) and an encryption method. It discusses how the LSB technique works by replacing the LSB of pixels in a cover image with bits from a secret image. It then proposes encrypting the LSB plane of the encoded image by altering its columns at regular intervals before generating the stego image. This increases security by making it harder to extract the secret image through steganalysis while maintaining image quality. MATLAB code demonstrates embedding a secret image in a cover image using LSB, encrypting the LSB plane, generating the stego image, and successfully extracting the secret image.
A robust combination of dwt and chaotic function for image watermarkingijctet
This document summarizes a research paper on a robust image watermarking technique that combines discrete wavelet transform (DWT) and a chaotic function. The proposed method embeds a watermark into selected blocks of the low-frequency DWT subband of an image. It calculates the Euclidean distance between blocks of the watermark and image to select the most similar block for embedding. Experimental results on standard test images show the proposed method achieves better performance than previous methods in terms of PSNR and structural similarity under compression attacks. The extraction accuracy remains high even with noise attacks, though it degrades more under filtering attacks.
IRJET- LS Chaotic based Image Encryption System Via Permutation ModelsIRJET Journal
This document proposes an image encryption system using logistic sine map and permutation models. The system works as follows:
1. A plain image is converted to grayscale and decomposed into 8 bit planes.
2. Each bit plane is randomly scrambled.
3. A logistic sine map is used to generate a key to partially encrypt each bit plane.
4. The bits planes are then permuted to obtain the final encrypted image. Logistic sine maps are well-suited for this approach due to their sensitivity to initial parameter values and ability to generate seemingly random outputs. The system aims to increase security by efficiently scrambling and permuting the bit plane values of the input image.
The document presents a method for human action recognition using both RGB and depth data from an RGB-D sensor. Motion History Images (MHIs) are generated from RGB videos and Depth Motion Maps (DMMs) are generated from depth data after rotating the 3D point clouds. A 4-channel Deep Convolutional Neural Network is trained with one channel for MHIs and three channels for the rotated DMM views. Evaluated on the UTD-MHAD dataset, the proposed method achieves better recognition accuracy when fusing both RGB and depth modalities compared to using each individually.
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.
A secured data transmission system by reversible data hiding with scalable co...IAEME Publication
The document describes a method for secure image transmission that combines reversible data hiding, encryption, compression, and steganography. It involves three main steps:
1. Reversible data hiding is used to embed the original image data by reserving room before encryption. Some pixel least significant bit values are embedded in other pixels.
2. Scalable compression is then applied to further secure the image.
3. The compressed, encrypted image then has additional data hidden within it using steganography techniques for transmission.
The receiving end performs the inverse processes of extracting the data, decompressing the image, and recovering the original embedded image in a lossless and secure manner. The method aims to achieve high quality encrypted
This document discusses image compression algorithms using the Lapped Orthogonal Transform (LOT) and Discrete Cosine Transform (DCT) under the JPEG standard. It begins with an introduction to image compression and classification of compression schemes. It then describes LOT and DCT in detail and proposes a hybrid algorithm using both transforms simultaneously. The algorithm is tested on an image and achieves a peak signal-to-noise ratio of 36.76 decibels at a bit rate of 0.6 bits per pixel, providing higher quality than DCT alone. The document concludes the hybrid approach offers better energy compaction and quality at low bit rates than DCT.
Cecimg an ste cryptographic approach for data security in imageijctet
The document presents a new algorithm called CECIMG (Canny edge encryption image steganography) for securing data in images. It combines Blowfish encryption with embedding encrypted data in the edge pixels of an image detected using Canny edge detection. The algorithm is implemented in Java and experiments show it provides better security and higher PSNR values than existing LSB steganography techniques. It securely stores encrypted data in images in a series of steps and allows retrieval of the original data. The algorithm aims to maximize security compared to traditional approaches.
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.
This document summarizes a research paper that proposes a new lossless image compression algorithm called Pixel Size Reduction (PSR). The PSR algorithm achieves compression by representing pixels using the minimum number of bits needed based on their frequency of occurrence in the image, rather than a fixed 8 bits per pixel. Experimental results on test images showed that the PSR algorithm achieved better compression ratios than other lossless compression methods like Huffman, TIFF, GPPM, and PCX. The paper compares the compressed file sizes of the PSR algorithm to these other methods on various synthetic images.
A NOVEL IMAGE STEGANOGRAPHY APPROACH USING MULTI-LAYERS DCT FEATURES BASED ON...ijma
Steganography is the science of hidden data in the cover image without any updating of the cover image.
The recent research of the steganography is significantly used to hide large amount of information within
an image and/or audio files. This paper proposed a new novel approach for hiding the data of secret image
using Discrete Cosine Transform (DCT) features based on linear Support Vector Machine (SVM)
classifier. The DCT features are used to decrease the image redundant information. Moreover, DCT is
used to embed the secrete message based on the least significant bits of the RGB. Each bit in the cover
image is changed only to the extent that is not seen by the eyes of human. The SVM used as a classifier to
speed up the hiding process via the DCT features. The proposed method is implemented and the results
show significant improvements. In addition, the performance analysis is calculated based on the
parameters MSE, PSNR, NC, processing time, capacity, and robustness.
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.
A High Performance Modified SPIHT for Scalable Image CompressionCSCJournals
In this paper, we present a novel extension technique to the Set Partitioning in Hierarchical Trees (SPIHT) based image compression with spatial scalability. The present modification and the preprocessing techniques provide significantly better quality (both subjectively and objectively) reconstruction at the decoder with little additional computational complexity. There are two proposals for this paper. Firstly, we propose a pre-processing scheme, called Zero-Shifting, that brings the spatial values in signed integer range without changing the dynamic ranges, so that the transformed coefficient calculation becomes more consistent. For that reason, we have to modify the initialization step of the SPIHT algorithms. The experiments demonstrate a significant improvement in visual quality and faster encoding and decoding than the original one. Secondly, we incorporate the idea to facilitate resolution scalable decoding (not incorporated in original SPIHT) by rearranging the order of the encoded output bit stream. During the sorting pass of the SPIHT algorithm, we model the transformed coefficient based on the probability of significance, at a fixed threshold of the offspring. Calling it a fixed context model and generating a Huffman code for each context, we achieve comparable compression efficiency to that of arithmetic coder, but with much less computational complexity and processing time. As far as objective quality assessment of the reconstructed image is concerned, we have compared our results with popular Peak Signal to Noise Ratio (PSNR) and with Structural Similarity Index (SSIM). Both these metrics show that our proposed work is an improvement over the original one.
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
The document summarizes a proposed user-friendly image sharing scheme that uses JPEG-LS prediction and LSB matching functions. The scheme encodes a secret image into meaningful shadow images using different prime numbers for different blocks, as determined by JPEG-LS prediction. It hides the prime number indicators in the least significant bits of pixels using LSB matching to prevent image degradation. The experimental results showed the reconstructed image quality was higher than previous schemes, making it suitable for applications requiring high quality images like medicine, military, or art.
COMPARISON OF SECURE AND HIGH CAPACITY COLOR IMAGE STEGANOGRAPHY TECHNIQUES I...ijait
This document compares color image steganography techniques in the RGB and YCbCr color spaces. It summarizes previous related work and then describes a proposed method that hides two grayscale images in a color image. For RGB, the secret images are hidden in the green and blue color channels by matching blocks and storing the locations in encrypted keys. For YCbCr, one secret image is hidden in the Cb channel and the other in the Cr channel in the same way. The keys are extracted during retrieval and used to reconstruct the secret images from the color channels. Experimental results show YCbCr provides better steganography than RGB in terms of security and quality of extracted secret images.
Design a New Image Encryption using Fuzzy Integral Permutation with Coupled C...IJORCS
This document proposes a new image encryption algorithm combining DNA sequence addition and coupled chaotic maps. The algorithm has two parts: 1) A DNA sequence matrix is obtained by encoding image pixels and divided into blocks that are added using Sugeno fuzzy integral, 2) The modified color components are encrypted using coupled two-dimensional piecewise nonlinear chaotic maps to strengthen security. Experimental results on image databases show the algorithm effectively protects digital image security over the internet.
This document discusses fractal image compression based on jointly and different partitioning schemes. It proposes partitioning RGB images into range blocks in two ways: 1) Jointly, where the red, green, and blue channels are partitioned together into blocks of the same size and coordinates. 2) Differently, where each channel is partitioned independently, resulting in different block sizes and coordinates for each channel. The document provides background on fractal image compression and the encoding/decoding processes. It analyzes the two partitioning schemes and argues the different scheme is more effective for encoding by allowing each channel to have customized partitioning.
Steganography is the technique of hiding the fact that communication is taking place,
by hiding data in other data. Many different carrier file formats can be used, but digital images
are the most popular because of their frequency on the Internet. For hiding secret information in
images, there exist a large variety of steganographic techniques. Steganalysis, the detection of this
hidden information, is an inherently difficult problem.In this paper,I am going to cover different
steganographic techniques researched by different researchers.
Keywords — Cryptography, Steganography, LSB, Hash-LSB, RSA Encryption –Decryption
Iaetsd implementation of lsb image steganography system using edge detectionIaetsd Iaetsd
This document proposes an image steganography system that uses edge detection, LZW compression, and hybrid encryption methods. It first encrypts the secret image using AES and ECC encryption. It then compresses the encrypted image using LZW compression. Next, it detects edges in the cover image using Canny edge detection. It then embeds the compressed encrypted image into the cover image by modifying the least significant bits of edge pixels. To decode, it extracts the embedded image, decompresses it, and decrypts it using ECC and AES decryption, recovering the original secret image. Evaluation results show the proposed method provides better security compared to existing methods while maintaining high quality of the stego image.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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
IRJET- Image based Approach for Indian Fake Note Detection by Dark Channe...IRJET Journal
This document presents a proposed method for detecting fake Indian currency notes using image processing techniques. The proposed system takes an image of a currency note as input and performs pre-processing including resizing, restoration, and enhancement. It then applies "X-ray vision" using dark channel prior to extract inner and outer edges of patterns in the image. The extracted patterns are labeled and classified using a fuzzy classifier. The system is able to classify images as real or fake currency with 90-95% accuracy. The document reviews related work on currency detection and provides details on the proposed methodology, which includes image acquisition, pre-processing, enhancement, dark channel prior, labeling, and fuzzy classification. Results are presented showing the output of each step.
Different Approach of VIDEO Compression Technique: A StudyEditor IJCATR
The main objective of video compression is to achieve video compression with less possible losses to reduce the
transmission bandwidth and storage memory. This paper discusses different approach of video compression for better transmission of
video frames for multimedia application. Video compression methods such as frame difference approach, PCA based method,
accordion function, fuzzy concept, and EZW and FSBM were analyzed in this paper. Those methods were compared for performance,
speed and accuracy and which method produces better visual quality.
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.
This document describes a wireless sensor network system using Zigbee technology for monitoring and controlling parameters like temperature, LPG gas, and light intensity in a gas plant. The system uses a coordinator to collect sensor data from nodes and provide it to the end user. It consists of sensor nodes with an ARM7 microcontroller connected to various sensors and a Zigbee module. The nodes transmit sensor data to sub-master nodes which relay the data to the main PC master using cooperative communication to ensure the slave nodes are always in range. The master displays the real-time sensor readings and logs the data for monitoring. The system provides benefits like low cost, low power consumption, remote monitoring and control capabilities.
This document discusses a proposed system for classifying audio scenes in action movies. It aims to provide scene recognition and detection by separating audio classes and obtaining better sound classification accuracy. The system extracts audio features like zero-crossing rate, short-time energy, volume root mean square, and volume dynamic range. It then uses hidden Markov models and support vector machines to classify audio scenes, labeling them as happy, miserable, or action scenes. Sound event types classified include gunshots, screams, car crashes, talking, laughter, fighting, shouting, and background crowd noise. The goal is to index and retrieve interesting events from action movies to engage viewers.
The document outlines the differences between wants and needs, with examples of each. It also distinguishes between goods, which are tangible items, and services, which are activities consumed as they are produced. Finally, it lists some natural resources such as wood, water, and wind.
This document discusses image compression algorithms using the Lapped Orthogonal Transform (LOT) and Discrete Cosine Transform (DCT) under the JPEG standard. It begins with an introduction to image compression and classification of compression schemes. It then describes LOT and DCT in detail and proposes a hybrid algorithm using both transforms simultaneously. The algorithm is tested on an image and achieves a peak signal-to-noise ratio of 36.76 decibels at a bit rate of 0.6 bits per pixel, providing higher quality than DCT alone. The document concludes the hybrid approach offers better energy compaction and quality at low bit rates than DCT.
Cecimg an ste cryptographic approach for data security in imageijctet
The document presents a new algorithm called CECIMG (Canny edge encryption image steganography) for securing data in images. It combines Blowfish encryption with embedding encrypted data in the edge pixels of an image detected using Canny edge detection. The algorithm is implemented in Java and experiments show it provides better security and higher PSNR values than existing LSB steganography techniques. It securely stores encrypted data in images in a series of steps and allows retrieval of the original data. The algorithm aims to maximize security compared to traditional approaches.
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.
This document summarizes a research paper that proposes a new lossless image compression algorithm called Pixel Size Reduction (PSR). The PSR algorithm achieves compression by representing pixels using the minimum number of bits needed based on their frequency of occurrence in the image, rather than a fixed 8 bits per pixel. Experimental results on test images showed that the PSR algorithm achieved better compression ratios than other lossless compression methods like Huffman, TIFF, GPPM, and PCX. The paper compares the compressed file sizes of the PSR algorithm to these other methods on various synthetic images.
A NOVEL IMAGE STEGANOGRAPHY APPROACH USING MULTI-LAYERS DCT FEATURES BASED ON...ijma
Steganography is the science of hidden data in the cover image without any updating of the cover image.
The recent research of the steganography is significantly used to hide large amount of information within
an image and/or audio files. This paper proposed a new novel approach for hiding the data of secret image
using Discrete Cosine Transform (DCT) features based on linear Support Vector Machine (SVM)
classifier. The DCT features are used to decrease the image redundant information. Moreover, DCT is
used to embed the secrete message based on the least significant bits of the RGB. Each bit in the cover
image is changed only to the extent that is not seen by the eyes of human. The SVM used as a classifier to
speed up the hiding process via the DCT features. The proposed method is implemented and the results
show significant improvements. In addition, the performance analysis is calculated based on the
parameters MSE, PSNR, NC, processing time, capacity, and robustness.
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.
A High Performance Modified SPIHT for Scalable Image CompressionCSCJournals
In this paper, we present a novel extension technique to the Set Partitioning in Hierarchical Trees (SPIHT) based image compression with spatial scalability. The present modification and the preprocessing techniques provide significantly better quality (both subjectively and objectively) reconstruction at the decoder with little additional computational complexity. There are two proposals for this paper. Firstly, we propose a pre-processing scheme, called Zero-Shifting, that brings the spatial values in signed integer range without changing the dynamic ranges, so that the transformed coefficient calculation becomes more consistent. For that reason, we have to modify the initialization step of the SPIHT algorithms. The experiments demonstrate a significant improvement in visual quality and faster encoding and decoding than the original one. Secondly, we incorporate the idea to facilitate resolution scalable decoding (not incorporated in original SPIHT) by rearranging the order of the encoded output bit stream. During the sorting pass of the SPIHT algorithm, we model the transformed coefficient based on the probability of significance, at a fixed threshold of the offspring. Calling it a fixed context model and generating a Huffman code for each context, we achieve comparable compression efficiency to that of arithmetic coder, but with much less computational complexity and processing time. As far as objective quality assessment of the reconstructed image is concerned, we have compared our results with popular Peak Signal to Noise Ratio (PSNR) and with Structural Similarity Index (SSIM). Both these metrics show that our proposed work is an improvement over the original one.
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
The document summarizes a proposed user-friendly image sharing scheme that uses JPEG-LS prediction and LSB matching functions. The scheme encodes a secret image into meaningful shadow images using different prime numbers for different blocks, as determined by JPEG-LS prediction. It hides the prime number indicators in the least significant bits of pixels using LSB matching to prevent image degradation. The experimental results showed the reconstructed image quality was higher than previous schemes, making it suitable for applications requiring high quality images like medicine, military, or art.
COMPARISON OF SECURE AND HIGH CAPACITY COLOR IMAGE STEGANOGRAPHY TECHNIQUES I...ijait
This document compares color image steganography techniques in the RGB and YCbCr color spaces. It summarizes previous related work and then describes a proposed method that hides two grayscale images in a color image. For RGB, the secret images are hidden in the green and blue color channels by matching blocks and storing the locations in encrypted keys. For YCbCr, one secret image is hidden in the Cb channel and the other in the Cr channel in the same way. The keys are extracted during retrieval and used to reconstruct the secret images from the color channels. Experimental results show YCbCr provides better steganography than RGB in terms of security and quality of extracted secret images.
Design a New Image Encryption using Fuzzy Integral Permutation with Coupled C...IJORCS
This document proposes a new image encryption algorithm combining DNA sequence addition and coupled chaotic maps. The algorithm has two parts: 1) A DNA sequence matrix is obtained by encoding image pixels and divided into blocks that are added using Sugeno fuzzy integral, 2) The modified color components are encrypted using coupled two-dimensional piecewise nonlinear chaotic maps to strengthen security. Experimental results on image databases show the algorithm effectively protects digital image security over the internet.
This document discusses fractal image compression based on jointly and different partitioning schemes. It proposes partitioning RGB images into range blocks in two ways: 1) Jointly, where the red, green, and blue channels are partitioned together into blocks of the same size and coordinates. 2) Differently, where each channel is partitioned independently, resulting in different block sizes and coordinates for each channel. The document provides background on fractal image compression and the encoding/decoding processes. It analyzes the two partitioning schemes and argues the different scheme is more effective for encoding by allowing each channel to have customized partitioning.
Steganography is the technique of hiding the fact that communication is taking place,
by hiding data in other data. Many different carrier file formats can be used, but digital images
are the most popular because of their frequency on the Internet. For hiding secret information in
images, there exist a large variety of steganographic techniques. Steganalysis, the detection of this
hidden information, is an inherently difficult problem.In this paper,I am going to cover different
steganographic techniques researched by different researchers.
Keywords — Cryptography, Steganography, LSB, Hash-LSB, RSA Encryption –Decryption
Iaetsd implementation of lsb image steganography system using edge detectionIaetsd Iaetsd
This document proposes an image steganography system that uses edge detection, LZW compression, and hybrid encryption methods. It first encrypts the secret image using AES and ECC encryption. It then compresses the encrypted image using LZW compression. Next, it detects edges in the cover image using Canny edge detection. It then embeds the compressed encrypted image into the cover image by modifying the least significant bits of edge pixels. To decode, it extracts the embedded image, decompresses it, and decrypts it using ECC and AES decryption, recovering the original secret image. Evaluation results show the proposed method provides better security compared to existing methods while maintaining high quality of the stego image.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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
IRJET- Image based Approach for Indian Fake Note Detection by Dark Channe...IRJET Journal
This document presents a proposed method for detecting fake Indian currency notes using image processing techniques. The proposed system takes an image of a currency note as input and performs pre-processing including resizing, restoration, and enhancement. It then applies "X-ray vision" using dark channel prior to extract inner and outer edges of patterns in the image. The extracted patterns are labeled and classified using a fuzzy classifier. The system is able to classify images as real or fake currency with 90-95% accuracy. The document reviews related work on currency detection and provides details on the proposed methodology, which includes image acquisition, pre-processing, enhancement, dark channel prior, labeling, and fuzzy classification. Results are presented showing the output of each step.
Different Approach of VIDEO Compression Technique: A StudyEditor IJCATR
The main objective of video compression is to achieve video compression with less possible losses to reduce the
transmission bandwidth and storage memory. This paper discusses different approach of video compression for better transmission of
video frames for multimedia application. Video compression methods such as frame difference approach, PCA based method,
accordion function, fuzzy concept, and EZW and FSBM were analyzed in this paper. Those methods were compared for performance,
speed and accuracy and which method produces better visual quality.
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.
This document describes a wireless sensor network system using Zigbee technology for monitoring and controlling parameters like temperature, LPG gas, and light intensity in a gas plant. The system uses a coordinator to collect sensor data from nodes and provide it to the end user. It consists of sensor nodes with an ARM7 microcontroller connected to various sensors and a Zigbee module. The nodes transmit sensor data to sub-master nodes which relay the data to the main PC master using cooperative communication to ensure the slave nodes are always in range. The master displays the real-time sensor readings and logs the data for monitoring. The system provides benefits like low cost, low power consumption, remote monitoring and control capabilities.
This document discusses a proposed system for classifying audio scenes in action movies. It aims to provide scene recognition and detection by separating audio classes and obtaining better sound classification accuracy. The system extracts audio features like zero-crossing rate, short-time energy, volume root mean square, and volume dynamic range. It then uses hidden Markov models and support vector machines to classify audio scenes, labeling them as happy, miserable, or action scenes. Sound event types classified include gunshots, screams, car crashes, talking, laughter, fighting, shouting, and background crowd noise. The goal is to index and retrieve interesting events from action movies to engage viewers.
The document outlines the differences between wants and needs, with examples of each. It also distinguishes between goods, which are tangible items, and services, which are activities consumed as they are produced. Finally, it lists some natural resources such as wood, water, and wind.
This document summarizes a research paper that describes the development and verification of a VHDL code for a 16-bit analog-to-digital converter (ADC) for an FPGA-based beam position measurement board. The board uses a Spartan-3 FPGA and 4-channel 16-bit ADC interfaced with a VME bus to digitize signals from a beam position indicator and store the data in onboard memory. The VHDL code for the ADC was developed and tested using various tools. Testing verified the functionality of the ADC, VME interface, and data acquisition.
The document describes the design and implementation of a 64-bit arithmetic logic unit (ALU) and compares its speed and power consumption on different field programmable gate arrays (FPGAs). Key aspects include:
1) The 64-bit ALU design supports 16 instructions and operates in a power-down mode when no instructions are available to reduce power consumption.
2) The design was simulated in Verilog and synthesized for an FPGA.
3) When implemented on different FPGAs, the design achieved speeds up to 203MHz on Spartan2 but consumed only 7mW of power, while Virtex 4 provided the highest speed of 597MHz but consumed 129mW.
The document discusses the design and implementation of optimal pulse shaping filters for digital radio systems. It specifically focuses on raised cosine and root raised cosine filters. These filters are used to reduce interference between symbols (ISI) and noise in the channel. The authors implement a 16-QAM digital communication system using these pulse shaping filters at the transmitter and matched filters at the receiver. Simulation results show that the root raised cosine filters help reduce bit error rates compared to raised cosine filters.
This document summarizes research on using graph partitioning techniques to solve digital circuit layout problems. It discusses how the digital circuit layout problem is a constrained optimization problem that is NP-hard. It then reviews previous work on using techniques like min-cut bipartitioning, multi-way partitioning algorithms, and spectral graph partitioning to solve the problem. The document concludes by analyzing evolutionary approaches that have been used, including genetic algorithms, memetic algorithms, ant colony optimization, and particle swarm intelligence. It finds that these approaches are dependent on representation and initialization but can produce quality solutions for small circuits.
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.
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.
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.
Comparative Performance of Image Scrambling in Transform Domain using Sinusoi...CSCJournals
With the rapid development of technology, and the popularization of internet, communication is been greatly promoted. The communication is not limited only to information but also includes multimedia information like digital Images. Therefore, the security of digital images has become a very important and practical issue, and appropriate security technology is used for those digital images containing confidential or private information especially. In this paper a novel approach of Image scrambling has been proposed which includes both spatial as well as Transform domain. Experimental results prove that correlation obtained in scrambled images is much lesser then the one obtained in transformed images.
Image Encryption Based on Pixel Permutation and Text Based Pixel Substitutionijsrd.com
Digital image Encryption techniques play a very important role to prevent image from unauthorized access. There are many types of methods available that can do Image Encryption, and the majority of them are scrambling algorithms based on pixel shuffling, which cannot change the histogram of an image. Hence, their security performances are not good. The encryption method that combines the pixel exchanging and gray level changing can handles reach a good chaotic effect. In this paper we focus on an image encryption technique based on pixel wise shuffling with the help of skew tent map and text based pixel substitution. The PSNR, NPCR and CC obtained by our technique shows that the proposed technique gives better result than the existing techniques.
Fast and Secure Transmission of Image by using Byte Rotation Algorithm in Net...IRJET Journal
This document proposes a new secure image transmission method using byte rotation algorithm that improves encryption speed and security. The key steps are:
1. The input image is divided into four blocks which are shuffled using byte rotation.
2. A cover image is used to embed the shuffled secret image blocks for transmission.
3. At the receiver, byte rotation is applied again to extract the original secret image blocks from the embedded image.
Experimental results show the proposed method recovers images with high PSNR quality scores while increasing encryption speed over other algorithms like AES. This provides a more secure and fast way to transmit encrypted images over networks.
EFFICIENT SCRAMBLING-SUBSTITUTION IMAGE SECURITY SCHEME USING CHAOTIC ARNOLD-...IJCNCJournal
This paper introduces an efficient scrambling-substitution image security scheme using chaotic Arnold and
Logistic (Arnold-Logistic) maps in the discrete cosine transform (DCT). The Arnold map is employed as a
scrambling stage while the Logistic map is employed as a substitution stage. The hybrid Arnold-Logistic
mapping is performed in the DCT. The encipherment phase of the introduced DCT-based Arnold-Logistic
security scheme begins by applying the DCT to the plainimage and the resulted DCT coefficient of the
plainimage are scrambled for m iterations using the Arnold transformation. Then, the Arnold-based
transformed DCT coefficients are substituted for n iterations using the Logistic map and the inverse of
DCT (IDCT) is employed to produce the cipherimage. The decipherment phase of the introduced DCTbased Arnold-Logistic security scheme is the inverse of the encryption stage and begins by applying the
DCT to the cipherimage. The resulted DCT coefficient of the cipherimage is inversely substituted for n
iterations using the inverse Logistic map. Then, the inverse Logistic-based transformed DCT coefficients
are inversely scrambled for m iterations using the inverse Arnold map and the IDCT is employed to
produce the decrypted image. A series of test experiments are applied to investigate the introduced DCTbased Arnold-Logistic security scheme. The outcome results demonstrated the superiority of the introduced
DCT-based Arnold-Logistic security scheme from the security point of view.
Efficient Scrambling-Substitution Image Security Scheme using Chaotic Arnold-...IJCNCJournal
A distributed denial of service (DDoS) attack is one of the most common cyber threats to the Internet of Things (IoT). Several deep learning (DL) techniques have been utilized in intrusion detection systems to prevent DDoS attacks. However, their performance is greatly affected by a large class imbalance nature of the training datasets as well as the presence of redundant and irrelevant features in them. This study proposes RTL-DL, a new framework for an effective intrusion detection model based on the random oversampling technique and the Tomek-Links sampling technique (RTL), to minimize the effects of data imbalance in the CICIDS2017 dataset used to evaluate the proposed model. This study achieved 98.3% accuracy, 98.8% precision, 98.3% recall, 97.8% f-score, and 4.6% hamming loss. In comparison to current approaches, the suggested model has demonstrated promising results in identifying network threats in imbalanced data sets.
This document proposes an adaptive steganography technique for hiding secret data in digital images. The technique uses variable bit length embedding based on wavelet coefficients of the cover image. A logistic map is used to generate a secret key, which determines the RGB color planes and blocks used for data hiding. Wavelet coefficients are classified into ranges, and the number of bits hidden corresponds to the coefficient value range. Extraction involves selecting the same coefficients based on the key and calculating the hidden bits. The technique aims to improve security, capacity and imperceptibility compared to existing constant bit length methods. Evaluation shows the proposed method provides good security since variable bits are hidden randomly using the secret key.
Reversible encrypted data concealment in images by reserving room approachIAEME Publication
The document summarizes a novel method for reversible encrypted data concealment in images. The proposed method reserves room in the original image before encryption using a traditional reversible data hiding algorithm like lifting wavelet transform. This makes it easy for a data hider to reversibly embed data in the encrypted image by simply filling the pre-reserved space. The method is compared to previous "vacating room after encryption" methods and shows it can embed over 10 times as large payloads with the same image quality, as well as achieve better performance in terms of PSNR and MSE. Experiments on test images demonstrate the benefits of the proposed "reserving room before encryption" approach.
Image Steganography Using HBC and RDH TechniqueEditor IJCATR
There are algorithms in existence for hiding data within an image. The proposed scheme treats the image as a whole. Here
Integer Cosine Transform (ICT) and Integer Wavelet Transform (IWT) is combined for converting signal to frequency. Hide Behind
Corner (HBC) algorithm is used to place a key at corners of the image. All the corner keys are encrypted by generating Pseudo
Random Numbers. The Secret keys are used for corner parts. Then the hidden image is transmitted. The receiver should be aware of
the keys that are used at the corners while encrypting the image. Reverse Data Hiding (RDH) is used to get the original image and it
proceeds once when all the corners are unlocked with proper secret keys. With these methods the performance of the stegnographic
technique is improved in terms of PSNR value.
A new partial image encryption method for document images using variance base...IJECEIAES
The proposed method partially and completely encrypts the gray scale Document images. The complete image encryption is also performed to compare the performance with the existing encryption methods. The partial encryption is carried out by segmenting the image using the Quad-tree decomposition method based on the variance of the image block. The image blocks with uniform pixel levels are considered insignificant blocks and others the significant blocks. The pixels in the significant blocks are permuted by using 1D Skew tent chaotic map. The partially encrypted image blocks are further permuted using 2D Henon map to increase the security level and fed as input to complete encryption. The complete encryption is carried out by diffusing the partially encrypted image. Two levels of diffusion are performed. The first level simply modifies the pixels in the partially encrypted image with the Bernoulli’s chaotic map. The second level establishes the interdependency between rows and columns of the first level diffused image. The experiment is conducted for both partial and complete image encryption on the Document images. The proposed scheme yields better results for both partial and complete encryption on Speed, statistical and dynamical attacks. The results ensure better security when compared to existing encryption schemes.
IRJET-Survey of Highly Secured Methods for Image Transmission using Image Seg...IRJET Journal
This document summarizes a research paper that proposes a new method for securely transmitting images using image segmentation, permutation, and multi-encryption techniques. It begins with an abstract that outlines encrypting images to protect confidential data from unauthorized access. It then provides background on encryption and discusses how traditional text encryption is not suitable for large image files. The proposed method segments an image, permutes the pixels using random numbers, and repeats the encryption multiple times for security. It claims this approach provides strong encryption with minimal data loss or computational costs compared to other methods.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
This document summarizes a research paper that proposes a new image encryption method using magnitude and phase manipulation with crossover and mutation approaches. The proposed method encrypts images in the frequency domain. It performs crossover operations to swap real and complex parts of frequency components. It also applies a mutation operation using NOT logic. This makes the encrypted image sensitive to key changes and difficult to decrypt without the key. The method is evaluated on different types of images and is shown to encrypt images with 84-98% efficiency depending on the image content. The authors conclude the method provides an efficient encryption scheme and future work could further improve encryption of images containing easily recognizable objects.
Symmetric Image Encryption Algorithm Using 3D Rossler System........................................................1
Vishnu G. Kamat and Madhu Sharma
Node Monitoring with Fellowship Model against Black Hole Attacks in MANET.................................... 14
Rutuja Shah, M.Tech (I.T.-Networking), Lakshmi Rani, M.Tech (I.T.-Networking) and S. Sumathy, AP [SG]
Load Balancing using Peers in an E-Learning Environment ...................................................................... 22
Maria Dominic and Sagayaraj Francis
E-Transparency and Information Sharing in the Public Sector ................................................................ 30
Edison Lubua (PhD)
A Survey of Frequent Subgraphs and Subtree Mining Methods ............................................................. 39
Hamed Dinari and Hassan Naderi
A Model for Implementation of IT Service Management in Zimbabwean State Universities ................ 58
Munyaradzi Zhou, Caroline Ruvinga, Samuel Musungwini and Tinashe Gwendolyn Zhou
Present a Way to Find Frequent Tree Patterns using Inverted Index ..................................................... 66
Saeid Tajedi and Hasan Naderi
An Approach for Customer Satisfaction: Evaluation and Validation ....................................................... 79
Amina El Kebbaj and A. Namir
Spam Detection in Twitter – A Review...................................................................................................... 92
C. Divya Gowri and Professor V. Mohanraj
This document proposes a new shape-adaptive reversible integer lapped transform (SA-RLT) method for region-of-interest (ROI) coding of 2D remote sensing images. SA-RLT performs better than other transforms like SA-DWT and SA-DCT. The method segments the ROI using a new algorithm rather than hand segmentation. It then designs a SA-RLT based ROI compression scheme using object-based set partitioned embedded block coding (OBSPECK). Experimental results show that SA-RLT compression outperforms DCT and DWT compression for remote sensing images. The method provides flexible bit rate control and allows lossless ROI coding without background areas.
Encryption is used to securely transmit data in open networks. Each type of data has its own features. With the rapid growth of internet, security of digital images has become more and more important. Therefore different techniques should be used to protect confidential image data from unauthorized access. In this paper an encryption technique based on elliptic curves for securing images to transmit over public channels will be proposed. Encryption and decryption process are given in details with an example. The comparative study of the proposed scheme and the existing scheme is made. Our proposed algorithm is aimed at better encryption of all types of images even ones with uniform background and makes the image encryption scheme more secure. The output encrypted images reveal that the proposed method is robust.
This document provides an overview and implementation details of a Bit-Plane Complexity Segmentation Steganography (BPCS) technique. The technique allows for high capacity information hiding by replacing "noise-like
Electrically small antennas: The art of miniaturizationEditor IJARCET
We are living in the technological era, were we preferred to have the portable devices rather than unmovable devices. We are isolating our self rom the wires and we are becoming the habitual of wireless world what makes the device portable? I guess physical dimensions (mechanical) of that particular device, but along with this the electrical dimension is of the device is also of great importance. Reducing the physical dimension of the antenna would result in the small antenna but not electrically small antenna. We have different definition for the electrically small antenna but the one which is most appropriate is, where k is the wave number and is equal to and a is the radius of the imaginary sphere circumscribing the maximum dimension of the antenna. As the present day electronic devices progress to diminish in size, technocrats have become increasingly concentrated on electrically small antenna (ESA) designs to reduce the size of the antenna in the overall electronics system. Researchers in many fields, including RF and Microwave, biomedical technology and national intelligence, can benefit from electrically small antennas as long as the performance of the designed ESA meets the system requirement.
This document provides a comparative study of two-way finite automata and Turing machines. Some key points:
- Two-way finite automata are similar to read-only Turing machines in that they have a finite tape that can be read in both directions, but cannot write to the tape.
- Turing machines have an infinite tape that can be read from and written to, allowing them to recognize recursively enumerable languages.
- Both models are examined in their ability to accept the regular language L={anbm|m,n>0}.
- The time complexity of a two-way finite automaton for this language is O(n2) due to making two passes over the
This document analyzes and compares the performance of the AODV and DSDV routing protocols in a vehicular ad hoc network (VANET) simulation. Simulations were conducted using NS-2, SUMO, and MOVE simulators for a grid map scenario with varying numbers of nodes. The results show that AODV performed better than DSDV in terms of throughput and packet delivery fraction, while DSDV had lower end-to-end delays. However, neither protocol was found to be fully suitable for the highly dynamic VANET environment. The document concludes that further work is needed to develop improved routing protocols optimized for VANETs.
This document discusses the digital circuit layout problem and approaches to solving it using graph partitioning techniques. It begins by introducing the digital circuit layout problem and how it has become more complex with increasing circuit sizes. It then discusses how the problem can be decomposed into subproblems using graph partitioning to assign geometric coordinates to circuit components. The document reviews several traditional approaches to solve the problem, such as the Kernighan-Lin algorithm, and discusses their limitations for larger circuit sizes. It also discusses more recent approaches using evolutionary algorithms and concludes by analyzing the contributions of various approaches.
This document summarizes various data mining techniques that have been used for intrusion detection systems. It first describes the architecture of a data mining-based IDS, including sensors to collect data, detectors to evaluate the data using detection models, a data warehouse for storage, and a model generator. It then discusses supervised and unsupervised learning approaches that have been applied, including neural networks, support vector machines, K-means clustering, and self-organizing maps. Finally, it reviews several related works applying these techniques and compares their results, finding that combinations of approaches can improve detection rates while reducing false alarms.
This document provides an overview of speech recognition systems and recent progress in the field. It discusses different types of speech recognition including isolated word, connected word, continuous speech, and spontaneous speech. Various techniques used in speech recognition are also summarized, such as simulated evolutionary computation, artificial neural networks, fuzzy logic, Kalman filters, and Hidden Markov Models. The document reviews several papers published between 2004-2012 that studied speech recognition methods including using dynamic spectral subband centroids, Kalman filters, biomimetic computing techniques, noise estimation, and modulation filtering. It concludes that Hidden Markov Models combined with MFCC features provide good recognition results for large vocabulary, speaker-independent, continuous speech recognition.
This document discusses integrating two assembly lines, Line A and Line B, based on lean line design concepts to reduce space and operators. It analyzes the current state of the lines using tools like takt time analysis and MTM/UAS studies. Improvements are identified to eliminate waste, including methods improvements, workplace rearrangement, ergonomic changes, and outsourcing. Paper kaizen is conducted and work elements are retimed. The goal is to integrate the lines to better utilize space and manpower while meeting manufacturing standards.
This document summarizes research on the exposure of microwaves from cellular networks. It describes how microwaves interact with biological systems and discusses measurement techniques and safety standards regarding microwave exposure. While some studies have alleged health hazards from microwaves, independent reviews by health organizations have found no evidence that exposure to microwaves below international safety limits causes harm. The document concludes that with precautions like limiting exposure time and using phones with lower SAR ratings, microwaves from cell phones pose minimal health risks.
This document summarizes a research paper that examines the effect of feature reduction in sentiment analysis of online reviews. It uses principle component analysis to reduce the number of features (product attributes) from a dataset of 500 camera reviews labeled as positive or negative. Two models are developed - one using the original set of 95 product attributes, and one using the reduced set. Support vector machines and naive Bayes classifiers are applied to both models and their performance is evaluated to determine if classification accuracy can be maintained while using fewer features. The results show it is possible to achieve similar accuracy levels with less features, improving computational efficiency.
This document provides a review of multispectral palm image fusion techniques. It begins with an introduction to biometrics and palm print identification. Different palm print images capture different spectral information about the palm. The document then reviews several pixel-level fusion methods for combining multispectral palm images, finding that Curvelet transform performs best at preserving discriminative patterns. It also discusses hardware for capturing multispectral palm images and the process of region of interest extraction and localization. Common fusion methods like wavelet transform and Curvelet transform are also summarized.
This document describes a vehicle theft detection system that uses radio frequency identification (RFID) technology. The system involves embedding an RFID chip in each vehicle that continuously transmits a unique identification signal. When a vehicle is stolen, the owner reports it to the police, who upload the vehicle's information to a central database. Police vehicles are equipped with RFID receivers. If a stolen vehicle passes within range of a receiver, the receiver detects the vehicle's ID signal and displays its details on a tablet. This allows police to quickly identify and recover stolen vehicles. The system aims to make it difficult for thieves to hide a vehicle's identity and allows vehicles to be tracked globally wherever the detection system is implemented.
This document discusses and compares two techniques for image denoising using wavelet transforms: Dual-Tree Complex DWT and Double-Density Dual-Tree Complex DWT. Both techniques decompose an image corrupted by noise using filter banks, apply thresholding to the wavelet coefficients, and reconstruct the image. The Double-Density Dual-Tree Complex DWT yields better denoising results than the Dual-Tree Complex DWT as it produces more directional wavelets and is less sensitive to shifts and noise variance. Experimental results on test images demonstrate that the Double-Density method achieves higher peak signal-to-noise ratios, especially at higher noise levels.
This document compares the k-means and grid density clustering algorithms. It summarizes that grid density clustering determines dense grids based on the densities of neighboring grids, and is able to handle different shaped clusters in multi-density environments. The grid density algorithm does not require distance computation and is not dependent on the number of clusters being known in advance like k-means. The document concludes that grid density clustering is better than k-means clustering as it can handle noise and outliers, find arbitrary shaped clusters, and has lower time complexity.
This document proposes a method for detecting, localizing, and extracting text from videos with complex backgrounds. It involves three main steps:
1. Text detection uses corner metric and Laplacian filtering techniques independently to detect text regions. Corner metric identifies regions with high curvature, while Laplacian filtering highlights intensity discontinuities. The results are combined through multiplication to reduce noise.
2. Text localization then determines the accurate boundaries of detected text strings.
3. Text binarization filters background pixels to extract text pixels for recognition. Thresholding techniques are used to convert localized text regions to binary images.
The method exploits different text properties to detect text using corner metric and Laplacian filtering. Combining the results improves
This document describes the design and implementation of a low power 16-bit arithmetic logic unit (ALU) using clock gating techniques. A variable block length carry skip adder is used in the arithmetic unit to reduce power consumption and improve performance. The ALU uses a clock gating circuit to selectively clock only the active arithmetic or logic unit, reducing dynamic power dissipation from unnecessary clock charging/discharging. The ALU was simulated in VHDL and synthesized for a Xilinx Spartan 3E FPGA, achieving a maximum frequency of 65.19MHz at 1.98mW power dissipation, demonstrating improved performance over a conventional ALU design.
This document describes using particle swarm optimization (PSO) and genetic algorithms (GA) to tune the parameters of a proportional-integral-derivative (PID) controller for an automatic voltage regulator (AVR) system. PSO and GA are used to minimize the objective function by adjusting the PID parameters to achieve optimal step response with minimal overshoot, settling time, and rise time. The results show that PSO provides high-quality solutions within a shorter calculation time than other stochastic methods.
This document discusses implementing trust negotiations in multisession transactions. It proposes a framework that supports voluntary and unexpected interruptions, allowing negotiating parties to complete negotiations despite temporary unavailability of resources. The Trust-x protocol addresses issues related to validity, temporary loss of data, and extended unavailability of one negotiator. It allows a peer to suspend an ongoing negotiation and resume it with another authenticated peer. Negotiation portions and intermediate states can be safely and privately passed among peers to guarantee stability for continued suspended negotiations. An ontology is also proposed to provide formal specification of concepts and relationships, which is essential in complex web service environments for sharing credential information needed to establish trust.
This document discusses and compares various nature-inspired optimization algorithms for resolving the mixed pixel problem in remote sensing imagery, including Biogeography-Based Optimization (BBO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). It provides an overview of each algorithm, explaining key concepts like migration and mutation in BBO. The document aims to prove that BBO is the best algorithm for resolving the mixed pixel problem by comparing it to other evolutionary algorithms. It also includes figures illustrating concepts like the species model and habitat in BBO.
This document discusses principal component analysis (PCA) for face recognition. It begins with an introduction to face recognition and PCA. PCA works by calculating eigenvectors from a set of face images, which represent the principal components that account for the most variance in the image data. These eigenvectors are called "eigenfaces" and can be used to reconstruct the face images. The document then discusses how the system is implemented, including preparing a face database, normalizing the training images, calculating the eigenfaces/principal components, projecting the face images into this reduced space, and recognizing faces by calculating distances between projected test images and training images.
This document summarizes research on using wireless sensor networks to detect mobile targets. It discusses two optimization problems: 1) maximizing the exposure of the least exposed path within a sensor budget, and 2) minimizing sensor installation costs while ensuring all paths have exposure above a threshold. It proposes using tabu search heuristics to provide near-optimal solutions. The research also addresses extending the models to consider wireless connectivity, heterogeneous sensors, and intrusion detection using a game theory approach. Experimental results show the proposed mobile replica detection scheme can rapidly detect replicas with no false positives or negatives.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
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Presentation of the OECD Artificial Intelligence Review of Germany
Ijarcet vol-2-issue-7-2223-2229
1. ISSN: 2278 – 1323
International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
Volume 2, Issue 7, July 2013
2223
www.ijarcet.org
Abstract— Digital images have found usage in many
applications. These images may contain confidential
information and need to be protected when stored on memory
or transmitted over networks. Many techniques have been
proposed to deal with this security issues. In this paper, we
propose a new security enhancement scheme for digital
images. The scheme employs two methods: Residue Number
System (RNS) to Decimal (R/D) encoding and decoding
using the moduli set and a modified
Arnold transform algorithm. The encryption process uses
RNS to Decimal (D/R) converter (encoder) to decompose a
plain image into three residual images. The residual images
are fused together and encrypted using the modified Arnold
transform. In the decryption process, the modified Arnold
transform is used to decrypt the cipher image which is then
decomposed into three residual images. An R/D converter
(decoder) is then used to recover the plain image. The
proposed scheme is simulated on digital images of different
sizes using MATLAB. The obtained results show that the
scheme can effectively encrypt and decrypt images without
lost of any inherent information. The scheme also offers firm
resistance to statistical attacks such as histogram,
brute-force, correlation coefficient and key sensitivity. It can
be applied to anyshape of image and allow unlimited number
of iterations to be performed as opposed to best known state
of the art.
Index Terms—D/R encoder, R/D decoder, residual image,
Residue Number System, Arnold transform.
I. INTRODUCTION
The security of information and digital images has become a
major concern for the past few decades due to the rapid
advancement in internet and networking technologies.
Images have found usage in diverse areas such as medical,
military, science, engineering, art, entertainment,
advertising, and education. With the increasing use of digital
techniques for transmitting and storing images, the
fundamental issue of protecting the confidentiality, integrity
as well as the authenticity of images has become a major
concern. Over the years, various hidden and secret
communication techniques aimed at addressing this need,
have been proposed [1-15].
A lot of image scrambling techniques have been developed to
improve the security level of hidden information [1-15].
Image scrambling techniques scramble the pixel location of
digital images in such a manner that theybecome chaotic and
indistinguishable [11]. These techniques generally use
several keys for encryption and decryption and without the
correct keys and an appropriate method and attackers cannot
access the secret information even if they are able to sniff the
medium. Hence, the message remains highly secured against
unauthorised access [11].
The traditional Arnold cat map has been extensively refined
to strengthen its security [3], [11, [13]. However, these
techniques mainly apply only to square images and their
strength lie on periodicity. The techniques also merely
scramble the pixel position of the image.
Mohammad [12] proposed a block-based transformation
algorithm based on the combination of image transformation
and an encryption and decryption algorithm called Blowfish.
Katherine [5] used both the Arnold Cat Map to shuffle pixel
values and Chen’s chaotic map to change the grayscale
values of the pixels. Musheer et al. [13] proposed a new
image encryption algorithm based on three different chaotic
maps. In [13], the plain-image is first decomposed into 8x8
size blocks and then the block based shuffling of image is
carried out using 2D Cat map. Chattopadhyay et al. [3]
proposed a novel algorithm for encoding digital images by
using a circle map with 3 parameters. The algorithm [3]
showed an increase in security against cipher-text-only,
chosen-plaintext and chosen-cipher-text attacks. Minati [11]
proposed an image scrambling map based on Fibonacci and
Lucas series which can be used in various spatial domain
image processing techniques of data hiding and secret
communications.
In this paper we focus on the security mechanism of digital
image namely encryption and decryption using a modified
Arnold transform and Residue Number System (RNS). We
propose in here an image encryption and decryption
algorithm using the moduli set and
demonstrate that the algorithms successfully hide and
recover the plain image without lost of any inherent
information.
The rest of the paper is structured as follows: a brief
discussion of Arnold transform and RNS is presented in
Section 2. A detailed discussion of the proposed scheme is
covered in Section 3. Section 4 presents experimental results
and discussion on the scheme. Finally, Sections 5 and 6 look
at the concluding remarks and future works, respectively.
Enhancement of the Security of a Digital Image
using the Moduli Set
S. Alhassan, K.A. Gbolagade
2. ISSN: 2278 – 1323
International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
Volume 2, Issue 7, July 2013
2224
www.ijarcet.org
II. BACKGROUND INFORMATION
A. Arnold Transform
The Arnold transform is defined as the transformation [11]
such that;
(1)
where, and N is the size of
the digital image. (x’, y’) is the new position of the original
pixel position (x, y) of the N x N plain-image.
A new image is produced when all the points are
manipulated by Equation (1).
B. Residue Number System (RNS)
RNS comprises a set of moduli which are independent of
each other. An integer is represented by the residue of each of
the modulus and arithmetic operations are based on residues
individually. The advantage of using the RNS over the
conversional system includes “carry-free” operation, fault
tolerance, parallelism and modularity. These inherent
features make RNS to be widely used in Digital Signal
Processing (DSP) applications such as digital filtering,
convolution, fast Fourier transform and image processing
[18].
Let be a set of positive integers all
greater than 1. is called a modulus, and the n-tuple set
is called a moduli set. Consider an
integer number . For each of the modulus in
, we have ,
(which will be denoted as ). Thus the number in this
system is represented as ,
.
Given the moduli set , the number 150 can be
represented in RNS as
,
and
. Thus, the RNS
representation of 150 is thus: .
To avoid redundancy, the moduli set must be pairwise
relatively prime. Thus, for ,
where means the greatest common divisor
of .
Let , then the RNS representation is unique
for any integer . is called the dynamic
range [18], [19].
A Decimal to Residue (D/R) converter (encoder) is needed in
order to convert a decimal number to RNS representation.
C. RNS to Weighted Conversion
A Residue to Decimal (R/D) converter (decoder) is required
in other to convert from a RNS to decimal. The two method
used to convert RNS to weighted system are the Chinese
Remainder Theorem (CRT) and the Mixed Radix
Conversion (MRC). The CRT is employed in this research.
The CRT is defined as follows [19].
Given a moduli set
with for and dynamic
range , then by the CRT an integer whose
RNS representation is can be
converted from its residue form as
, (2)
where and is the multiplicative inverse of
with respect to .
A schematic diagram of the CRT is showed in Fig. 1.
Fig. 1. Schematic diagram of the CRT
For example, given the moduli set ,
, ,
Therefore by the CRT
Hence;
III. PROPOSED SCHEME
Encryption and decryption algorithms are formulated by
integrating a modified Arnold’s transform algorithm, and
the Chinese Remainder Theorem (CRT). The algorithms are
tested on both grayscale and true color images of varying
sizes through simulating with MATLAB.
3. ISSN: 2278 – 1323
International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
Volume 2, Issue 7, July 2013
2225
www.ijarcet.org
A. Encryption process
The encryption algorithm takes a plain image and transforms
it into a cipher image. The inputs to the algorithm are
(for moduli set), (a constant), (number
iterations) and (an plain image). The output of
this algorithm is an augmented cipher
image .
1) Pixel Encoding
The encoding process transforms an plain image
into an augmented encoded image by
using Equation (3).
2) Pixel Scrambling
The augmented image is then randomised by using the
modified Arnold transform presented in Equation (4) into
cipher image ;
(4)
where correspond
to the moduli set ,
and is vector refers to the size
of the image.
3) The Encryption Algorithm
The algorithm for the encryption process is as follows:
1) Input
2) Obtain the values of using
3) Using Equation (3), transform into the
augmented image .
4) For
Scramble into the cipher image using
Equation (4)
4) Save
A flow diagram of the encryption process is shown in Fig. 2.
Fig. 2. Flow diagram of the encryption process.
B. Decryption Process
The decryption process is a reverse of the encryption process.
It takes an cipher image and transforms it
into an plain image. This process has three stages;
anti-Arnold’s transform, decomposition process, and
decoding using CRT.
1) Pixel Scrambling
The pixels positions of the cipher image have to be
reorganised. This is achieved by applying Equation (4) in
reverse order. In doing this, the pixel values are returned to
their respective original positions to form the cipher
image .
2) Cipher Image Decomposition
The cipher image resulting from
scrambling process is decomposed into three cipher
images as follows in Equations (5),(6), and (7);
Let be decomposed cipher
images and the dimension of then,
(5)
(6)
(7)
In Equations (5), (6) and (7) respectively isolates three cipher
images corresponding to each of the three modulus
operations in Equation (3).
3) Pixel Decoding Using CRT
The three residual images obtained in the decomposition
process are then used to recover the pixels of the plain image.
In this regard, we implement Equation (2) using the pixels of
the decomposed images . Thus;
Given that are the residues of each original pixel
in with respect to then,
(8)
where and
, and
4) The Decryption Algorithm
The decryption algorithm is formulated as follows:
1) Input
2) Obtain using
3) For down to 1
Scramble into using Equation
4) Decompose into using
Equations (5), (6) and (7)
4) Using Equations (2) and (8) recover the
plain image from
6) Save
The complete decryption process is shown in Fig. 3.
Pixel
Encoding
Pixel
Scrambling
4. ISSN: 2278 – 1323
International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
Volume 2, Issue 7, July 2013
2226
www.ijarcet.org
Fig. 3. Flow diagram of the encryption process.
IV. EXPERIMENTAL RESULTS
In this section, a detail analysis of the proposed scheme has
been summarized. Simulations were conducted using
MALTAB. The analyses include visual testing, encoding
analysis and security analysis. Experimental results suggest
that the proposed scheme is more efficient than the proposal
in Minati, et al [11] in terms of encoding and security.
A. Visual Testing
Three images of varying size, both grayscale and colour were
used. Fig. 4 depicts test results for the images (lena (512 x
512), koala (448 x 336) and checkerboard (256 x 256)). The
visual test clearly shows the absence of similarities among
the pairs of images.
Fig. 4. Original and encrypted images
for .
Visual tests were also performed to check whether the
proposed scheme totally recovers plain images. Fig. 5 shows
the histograms of both original and decrypted images. It can
be seen from the similarities of both histograms that the
proposed scheme totally recovers plain images.
Fig. 5. Histograms of original and decrypted
images . (a) Original “lena”
histogram (upper left), (b) Decrypted “lena” histogram
(upper right), (c) Original “koala” histogram (middle left),
(d) Decrypted “koala” histogram (middle right) , (e) Original
“checkerboard” histogram (bottom left), (f) Decrypted
“checkerboard” histogram (bottom right).
B. Encoding Analysis
The pixel encoding during the encryption process achieves
two results. It reduces the pixel value and the size (in terms of
disk space) of the plain image but retains its physical. The
reduction in pixel value speeds up computation which is
useful during other image processing techniques. On the
other hand the reduction in size speeds up data transmission
across network since fewer bits are required to represent the
pixels. Table I compare the size of both plain and cipher
images when save in a JPEG format. It can be deduced from
the table that for the proposed system achieves a
reduction in size by up to 90%.
Table I. Disk sizes of plain and cipher images compared
Image Type Size(disk space)
Plain
image
Cipher
image
Compression
ratio
lena.jpg(512x512)grayscale 152 kb 26.7 kb 82.43%
Easy.bmp(640x480) colour 301 kb 31.7 kb 92.45%
pic.png(320x301) colour 163 kb 7.06 kb 95.66%
Pixel
Decoding
Pixel
Scrambling
5. ISSN: 2278 – 1323
International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
Volume 2, Issue 7, July 2013
2227
www.ijarcet.org
C. Security Analysis
In this subsection, we analyse the security and strength of our
encryption scheme. Areas assessed include histogram
analysis, keyspace, keysensitivityand correlation coefficient
analysis
1) Histogram Analysis
The histogram of an image refers to a histogram of the pixel
intensity value. It is a graph that shows the number of pixels
in an image at each different intensity value found in that
image. A cipher image is more secured against statistical
attack when its histogram conceals anyinformation about the
plain image and also completely defers from the histogram of
its plain image. Fig. 6 shows the histograms of a plain image
and its cipher image. It is very apparent from the figure that
the two histograms are completely different and thus the
histogram of the cipher image does not give any clue about
the plain image. This implies that the proposed system is
secure against histogram attack.
Fig. 6. Histograms of plain and encrypted “lena” images. (a)
Original image (upper left), (b) Encrypted image (upper
right), (c) Original histogram (bottom left), (d) Encrypted
histogram (bottom right).
2) Key Space Analysis
The brute-force attack is computationally infeasible for
cryptosystems with sufficiently large key space. The
proposed scheme uses a combination of three cipher
keys . The scheme achieves an efficient encoding
goal when . As and
a wide range of combination can be made.
However, we adapt a 56 bits key for as used in
Data Encryption Standard (DES). This gives us
possible
combination. Also, suppose an adversary try guessing a key
combination with a 1000 MIPS computer, then he/she
has . Clearly
this is a long enough time to resist brute-force attack.
3) Key Sensitivity Analysis
A good cryptosystem should be sensitive to the cipher key. A
slight change in the key value should lead to a significant
change in either plain image or cipher image. In this respect,
we present two results to illustrate the key sensitivity of the
proposed scheme. The first result shown in Fig. 5 shows that
the proposed scheme can successfullydecrypt images without
any loss of inherent information. On the other hand Fig. 7
shows decrypted images of Fig. 4 (b) with a different value of
one of the parameter while maintaining the other two. The
unsuccessful decrypted images attest to the fact that the
proposed scheme is sensitive to the cipher keys.
Fig. 7. Key sensitivity analysis (a) Decrypted image with
(b) Decrypted image with (c) Decrypted
image with
4) Correlation Coefficient Analysis
A digital image is meaningful to human vision if there is a
high correlation among adjacent pixels. Disturbing this
relationship will affect the visual identity of the image.
Among the requirements of an effective encryption scheme is
creating cipher images that have significantly low
correlation coefficient values. For this analysis, we computed
the correlation coefficients of randomly selected 1000 pairs
of two adjacent pixels (horizontal, vertical and diagonal) of
both plain and cipher images.
The correlation coefficient of pairs of adjacent pixels is as
follows [21]:
, (9)
with and
where represent grayscale value of adjacent pixels
in the image, and
,
,
6. ISSN: 2278 – 1323
International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
Volume 2, Issue 7, July 2013
2228
www.ijarcet.org
,
Applying Equation (9) on a 512 x 512 ‘lena.jpg’ grayscale
image gives the high correlation coefficient values of
0.97184002, 0.98309393, and 0.94877370, respectively for
horizontal, vertical and diagonal pairs of adjacent pixels.
Table II shows the corresponding correlation coefficient
values of cipher images generated for and
varying values of . The result shows that the cipher images
have weak correlation coefficient values (approximately
zero) among pairs of adjacent pixels.
Table II Correlation coefficients of adjacent pixels of a cipher
image
iteration Adjacent pixels
Horizontal Vertical Diagonal
1 0.02520737 0.06345870 0.03856429
2 0.03821026 0.01262754 0.04166987
3 0.02623524 0.00114685 -0.01844500
10 0.08843156 -0.01475551 0.01968406
15 -0.02460013 -0.02508439 0.01222209
V. CONCLUSION
In this paper, a new image encryption algorithm has been
presented. We hold the idea that the security of a
cryptosystem would be strengthened if pixel scrambling is
fused with encoding. Thus, the proposed scheme has two
major parts; pixel value encoding/decoding and pixel
scrambling. Experimental results reveal the following;
a) cipher images requires fewer number of bits to
represent pixels.
b) the scheme strongly resist to statistical attacks
(brute-force, correlation coefficient and histogram.
c) decryption does not depend on periodicity. Thus
the number of iterations to conduct is at the
discretion of the user.
d) the scheme is also highly sensitive to a small
change in any of the cipher keys.
The above mentioned points make our proposed scheme
outperform that proposed by Minati, et al [13].
VI. FUTURE WORK
Even though the proposed scheme is efficient in the areas
mentioned above, its drawback is the augmented cipher
image produced. Thus, cipher images require three times the
original memory allocation. A 512 x 512 plain image using
262144 bytes of memory allocation results in a 1536 x 512
(i.e. 512*3 x 512) cipher image using 786432 bytes.
Reducing the size of the cipher image without lost any
inherent information has been left as a subject of future
investigation.
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7. ISSN: 2278 – 1323
International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
Volume 2, Issue 7, July 2013
2229
www.ijarcet.org
[17]V.A.M. Pemmaraj, “RNS-To-Binary Converter for a
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S. Alhassan, Department of Computer Science, Faculty of
Mathematical Sciences, University for Development Studies,
Navrongo, Ghana.
Professor K.A. Gbolagade, Department of Computer
Science, Faculty of Mathematical Sciences, University for
Development Studies, Navrongo, Ghana.