Hybrid Chaotic Map Research Articles

Hybrid chaotic map with L-shaped fractal Tromino for image encryption and decryption

Insecure communication in digital image security and image storing are considered as important challenges. Moreover, the existing approaches face problems related to improper security at the time of image encryption and decryption. In this research work, a wavelet environment is obtained by transforming the cover image utilizing integer wavelet transform (IWT) and hybrid discrete cosine transform (DCT) to completely prevent false errors. Then the proposed hybrid chaotic map with L-shaped fractal Tromino offers better security to maintain image secrecy by means of encryption and decryption. The proposed work uses fractal encryption with the combination of L-shaped Tromino theorem for enhancement of information hiding. The regions of L-shaped fractal Tromino are sensitive to variations, thus are embedded in the watermark based on a visual watermarking technique known as reversible watermarking. The experimental results showed that the proposed method obtained peak signal-to-noise ratio (PSNR) value of 56.82dB which is comparatively higher than the existing methods that are, Beddington, free, and Lawton (BFL) map with PSNR value of 8.10 dB, permutation substitution, and Boolean operation with PSNR value of 21.19 dB and deoxyribonucleic acid (DNA) level permutation-based logistic map with PSNR value of 21.27 dB.

Security analysis of encrypted audio based on elliptic curve and hybrid chaotic maps within GFDM modulator in 5G networks

Wireless communications face significant security challenges, so there is an ongoing necessity to develop an appropriate security strategy to protect data from eavesdroppers using cryptography based on chaos theory. Generalized frequency division multiplexing (GFDM) is a modern multicarrier waveform adaptable to 5G requirements, but its security issues have not been considered. Therefore, this paper proposed an efficient security technique within the GFDM modulator to protect the audio transmission against eavesdropping in 5G networks. The proposed GFDM is achieved by separating the subsymbols for the subcarrier into real and imaginary parts and combining them using a mixture of elliptic curve-linear congruential generator sequence (EC-LCG) with Ikeda and Tent maps, respectively. After that, the subsymbols of each subcarrier are permuted independently using the Duffing map. The effectiveness of the proposed approach to resist attacks was tested, and findings that were achieved are histogram, signal to noise ratio (SNR=-27.8068), spectral segment SNR (SSSNR=-34.9912), peak SNR (PSNR=0.9142), frequency weighted log spectral distance (dFWLOG=37.498), cepstral distance (dCD=9.0176), mean square error (MSE=0.82097), keyspace, and speed. These results show that the proposed model provides a high-security level, high speed in the encryption/decryption, large keyspace, and high sensitivity to the initial conditions.

Image Encryption Using a New Hybrid Chaotic Map and Spiral Transformation.

Image encryption based on chaotic maps is an important method for ensuring the secure communication of digital multimedia on the Internet. To improve the encryption performance and security of image encryption systems, a new image encryption algorithm is proposed that employs a compound chaotic map and random cyclic shift. First, a new hybrid chaotic system is designed by coupling logistic, ICMIC, Tent, and Chebyshev (HLITC) maps. Comparison tests with previous chaotic maps in terms of chaotic trajectory, Lyapunov exponent, and approximate entropy illustrate that the new hybrid chaotic map has better chaotic performance. Then, the proposed HLITC chaotic system and spiral transformation are used to develop a new chaotic image encryption scheme using the double permutation strategy. The new HLITC chaotic system is used to generate key sequences used in the image scrambling and diffusion stages. The spiral transformation controlled by the chaotic sequence is used to scramble the pixels of the plaintext image, while the XOR operation based on a chaotic map is used for pixel diffusion. Extensive experiments on statistical analysis, key sensitivity, and key space analysis were conducted. Experimental results show that the proposed encryption scheme has good robustness against brute-force attacks, statistical attacks, and differential attacks and is more effective than many existing chaotic image encryption algorithms.

Novel hybrid chaotic map-based secure data transmission between smart meter and HAN devices

ABSTRACT Home area network (HAN) devices send the electricity consumption and other important data to the smart meter that must remain confidential from other devices. This paper proposes a novel one-dimensional hybrid chaotic map. The proposed map shows excellent chaotic properties when analyzed by bifurcation diagram, Lyapunov exponent & Shannon entropy. We further design an encryption strategy for data transfers between the smart meter and HAN devices. The proposed encryption scheme uses the existing lightweight key management in advanced metering infrastructure (LKM-AMI) architecture for data transfers, in which the encrypted data is transferred through an insecure channel and private keys are provided by trusted third party (TTP) through secure channels. The 2-way communication between HAN devices and the smart meter sends messages that are encrypted by using the proposed novel hybrid one-dimensional chaotic map. The encryption strategy mainly consists of three steps. In the first step, the seed and the control parameters are initialized. The second phase generates two intermediate keys using the proposed hybrid chaotic map. In the last phase, we encrypt the message by applying permutation followed by diffusion using intermediate keys. The proposed encryption strategy is resistant to various attacks.

Image encryption using a novel hybrid chaotic map and dynamic permutation−diffusion

Image encryption using a novel hybrid chaotic map and dynamic permutation−diffusion

A Multi-Strategy Crazy Sparrow Search Algorithm for the Global Optimization Problem

A multi-strategy crazy sparrow search algorithm (LTMSSA) for logic-tent hybrid chaotic maps is given in the research to address the issues of poor population diversity, slow convergence, and easily falling into the local optimum of the sparrow search algorithm (SSA). Firstly, the LTMSSA employs an elite chaotic backward learning strategy and an improved discoverer-follower ratio factor to improve the population’s quality and diversity. Secondly, the LTMSSA updates the positions of discoverers and followers by the crazy operator and the Lévy flight strategy to expand the selection range of target following individuals. Finally, during the algorithm’s optimization search, the LTMSSA introduces the tent hybrid and Corsi variable perturbation strategies to improve the population’s ability to jump out of the local optimum. Different types and dimensions of test functions are used as performance benchmark functions to test the performance of the LTMSSA with SSA variants and other algorithms. The simulation results show that the LTMSSA can jump out of the optimal local solution, converge faster, and have higher accuracy. Its overall performance is better than the other seven algorithms, and the LTMSSA can find smaller optimal values than other algorithms in the welded beam and reducer designs. The results confirm that the LTMSSA is an effective aid for computationally complex practical tasks, provides high-quality solutions, and outperforms other algorithms.

Secured Transfer and Storage Image Data for Cloud Communications

In cloud computing, resources are used to communicate instead of local servers or individual devices. However, sharing resources among several users is a difficult issue in cloud communication. Cryptography and steganography techniques are used for cloud storage to address data security challenges. This paper presents a novel method for securely encrypting image data for transmission and link exchange with a cloud storage service. There are two phases to accomplish the encryption process, the first phase encrypts the image file by XORing it with a random key that is generated by a new hybrid of the chaotic map. The second phase converts the encrypted image format to audio format to add another layer of security and improve secure image data transfer. The random key is generated using a hybrid chaotic map and has the benefit of having more than 10256 key spaces and the necessary level of security. Based on a statistical analysis of the encryption, the quality of the image is evaluated using several criteria, and the results demonstrate the algorithm's ability to accomplish resist encryption

Optimized Deep Learning-Enabled Hybrid Logistic Piece-Wise Chaotic Map for Secured Medical Data Storage System

Background: In recent times, medical technology has generated massive reports such as scanned medical images and electronic patient accounts. These reports are necessary to be stored in the highly secured platform for further reference. Traditional storage systems are infeasible for storing massive data. In addition, it suffers to provide secure storage and privacy protection at the time of medical services. It is necessary to provide secure storage and full utilization of personal medical records for the common people in practice. The healthcare system based on IoT enhances the support for the patients and doctors in diagnosing the sufferers at an accurate time using the monitored health data. Yet, doctors make an inappropriate decision regarding the sufferer’s sickness when the information regarding health data saved in the cloud gets lost or hacked owing to an external attack or also power failure. Hence, it is highly essential for verifying the truthfulness of the sufferer’s information regarding health data saved on the cloud.Hypothesis: The major intention of this task is to adopt a new chaotic-based healthcare medical data storage system for storing medical data (medical images) with high protection. Methodology: Initially, the input medical images are gathered from the benchmark datasets concerning different modalities. The collected medical images are enciphered by developing Hybrid Chaotic Map by adapting the 2D-Logistic Chaotic Map (2DLCM), and Piece-Wise Linear Chaotic Map (PWLCM) referred to as Hybrid Logistic Piece-Wise Chaotic Map (HLPWCM). An Optimized Recurrent Neural Network (O-RNN) is proposed for key generation using Best Fitness-based Coefficient vector improved Spotted Hyena Optimizer (BF-CSHO). The O-RNN-based key generation utilizes the extracted image features like first and second-order statistical features and the targets are acquired as a unique encrypted key, which is used for securing the medical data. The same BF-CSHO is used for improving the training algorithm (weight optimization) of RNN to minimize the Mean Absolute Error (MAE) between the cipher (encrypted) images and original images. Results: From the result analysis, the suggested BF-CSHO-RNN-HLPWCM, by considering the image size at [Formula: see text] shows 10.4%, 8.5%, 3.97%, 0.62%, 3.88%, 2.40%, and 7.82% provides better computational efficiency than LCM, PWLCM, LPWCM, PSO-RNN-HLPWCM, JA-RNN-HLPWCM, GWO-RNN-HLPWCM, and SHO-RNN-HLPWCM, respectively. Conclusion: Thus, the simulation findings show the effective efficiency of the offered method owing to the security of the stored medical data.

A novel image encryption algorithm based on hybrid chaotic maps using a key image

One of the most important data currently shared on the Internet is images of various sizes and types, gray and color, private and public, civilian and military, medical and scientific, commercial, and others. The biggest challenge and problem is the secure transmission of these images in this insecure environment. In this context, this paper proposes a new image encryption algorithm using a hybrid of three modified and improved chaotic one-dimensional (1D) maps to avoid the shortcomings of 1D maps and multidimensional (MD) maps. A key image is used to initialize the chaotic maps and is also used as a mask in the diffusion phase with the eXclusive OR (XOR) operator. The encryption process uses ExtraParam extracted from the original image, which is very sensitive to bit changes during the initialization of the chaotic maps. The proposed encryption process consists of two main phases: confusion and diffusion processes. The proposed image encryption algorithm has successfully passed numerous tests and cryptanalysis. We also measure the proposed algorithm with various analysis experiments such as histogram and entropy analysis, the number of pixel change rate (NPCR), the unified average changing intensity (UACI), the mean square error(MSE), the peak signal-to-noise ratio (PSNR) and Key Space. The experimental results and comparative analysis show that the proposed encryption algorithm has excellent performance, is strong enough to withstand various attacks, and provides excellent privacy to digital images.

Video Encryption Technique Based on Hybrid Chaotic Maps and Multi- Operation keys

Video Encryption Technique Based on Hybrid Chaotic Maps and Multi- Operation keys

Image encryption algorithm based on improved Zigzag transformation and quaternary DNA coding

Image security becomes increasingly critical as the multimedia technology and Internet of things evolve rapidly. To ensure image security and improve the efficiency of image encryption, a novel image encryption algorithm is proposed in this paper. Firstly, a novel one-dimensional hybrid chaotic map is proposed and employed to obtain the chaotic sequences to be used in the permutation and diffusion processes. Secondly, an improved Zigzag transformation is employed to permute the plain image. Thirdly, the dynamic quaternary DNA coding and operations are used to diffuse the permuted image. In the diffusion process, the DNA encoded image is permuted using the index sequence to further enhance the permutation effect. Finally, a look-up table method is proposed to quickly obtain the DNA operation results. The experimental results and the security analyses illustrate that the proposed algorithm has an excellent performance in terms of encryption effect, key space, key sensitivity, statistical performance, differential attack, encryption quality, robustness, execution time and computational complexity. Therefore, the proposed algorithm can be applied to some fields with high confidentiality requirements, such as military, commercial and medical fields.

Graph signal processing and tunicate swarm optimization based image steganography using hybrid chaotic map based image scrambling

This paper put forwards a secure image steganography technique for transmitting sensitive data using a Tunicate swarm optimization algorithm. A hybrid chaotic map-based image scrambling method is proposed with the combination of Tent and Tinkerbell chaotic maps. The scrambling of the secret image provides an added level of security in data hiding. The graph signal processing of cover image using the Meyer wavelet filter is performed to conceal the secret data within the transformed cover image using the alpha blending operation. To discover the optimal value of alpha for alpha blending, the tunicate swarm optimization algorithm is employed. To take the hidden information out at receiver end, the reverse approach is applied. The experimental results revealed that the embedding technique using the tunicate algorithm with a hybrid chaotic map provides better imperceptibility and robustness in comparison to the existing graph signal-based image steganography technique. The investigation is done on PSNR, MSE and SSIM performance parameters for evaluating the proposed technique.

Novel lightweight video encryption method based on ChaCha20 stream cipher and hybrid chaotic map

<span lang="EN-US">In the recent years, an increasing demand for securing visual resource-constrained devices become a challenging problem due to the characteristics of these devices. Visual resource-constrained devices are suffered from limited storage space and lower power for computation such as wireless sensors, internet protocol (IP) camera and smart cards. Consequently, to support and preserve the video privacy in video surveillance system, lightweight security methods are required instead of the existing traditional encryption methods. In this paper, a new light weight stream cipher method is presented and investigated for video encryption based on hybrid chaotic map and ChaCha20 algorithm. Two chaotic maps are employed for keys generation process in order to achieve permutation and encryption tasks, respectively. The frames sequences are encrypted-decrypted based on symmetric scheme with assist of ChaCha20 algorithm. The proposed lightweight stream cipher method has been tested on several video samples to confirm suitability and validation in term of encryption–decryption procedures. The performance evaluation metrics include visual test, histogram analysis, information entropy, correlation analysis and differential analysis. From the experimental results, the proposed lightweight encryption method exhibited a higher security with lower computation time compared with state-of-the-art encryption methods.</span>

Secure Image Encryption Using Chaotic, Hybrid Chaotic and Block Cipher Approach.

Secure image transmission is one of the most challenging problems in the age of communication technology. Millions of people use and transfer images for either personal or commercial purposes over the internet. One way of achieving secure image transmission over the network is encryption techniques that convert the original image into a non-understandable or scrambled form, called a cipher image, so that even if the attacker gets access to the cipher they would not be able to retrieve the original image. In this study, chaos-based image encryption and block cipher techniques are implemented and analyzed for image encryption. Arnold cat map in combination with a logistic map are used as native chaotic and hybrid chaotic approaches respectively whereas advanced encryption standard (AES) is used as a block cipher approach. The chaotic and AES methods are applied to encrypt images and are subjected to measures of different performance parameters such as peak signal to noise ratio (PSNR), number of pixels change rate (NPCR), unified average changing intensity (UACI), and histogram and computation time analysis to measure the strength of each algorithm. The results show that the hybrid chaotic map has better NPCR and UACI values which makes it more robust to differential attacks or chosen plain text attacks. The Arnold cat map is computationally efficient in comparison to the other two approaches. However, AES has a lower PSNR value (7.53 to 11.93) and has more variation between histograms of original and cipher images, thereby indicating that it is more resistant to statistical attacks than the other two approaches.

TWO LEVEL IMAGE CRYPTOSYSTEM USING HYBRID-CHAOTIC KEY AND PRNG KEY FOR MULTI-MODALITY DIGITAL IMAGES WITH DISCRETE WAVELET TRANSFORM

In this information age, the need of secure picture transmission is critical. Medical data is hacked in the form of photographs, which costs more in terms of insurance claims. It is vital to safeguard photographs so that unauthorised individuals cannot view them. Chaos-based picture crypto systems are the most well-known of the several types of image crypto systems because their keys are invulnerable to assault or hacking. The chaotic features play a significant role in the development of keys for secure transmission and reception. The discrete wavelet transform (DWT) is a more basic transform that compresses the input image by combining approximation and detailed coefficients. The incorporation of the key in the approximate coefficients of the input image provides an efficient encryption when compared to other image crypto schemes. A two level image encryption is adopted in this work, where one level is achieved using the hybrid-chaotic sequences and the next level is utilizing the pseudo random noise sequence (PRNG) as the keys. A smaller value of variance value is achieved which shows the higher uniformity of pixel values in encrypted images of our proposed two level image cryptography. Also the better performance metrics in terms of entropy, NPCR, and UACI are achieved compared to a single level image encryption. The developed image crypto system is designed and simulated using MATLAB software package. KEYWORDS: two level chaos image cryptosystems, DWT, encryption, hybrid-chaotic maps, and PRNG key generation.

An Enhanced Hybrid Chaotic Technique for Protecting Medical Images

Medical data has attracted much interest; a quick, lossless, and secure cryptosystem is required for saving and transferring images over open networks while maintaining the image's details. This paper shows how to protect medical images with an encryption method based on hybrid chaotic maps. The proposed hybrid method is constructed to deal with problems like confusion and diffusion with a large key space. The technique uses a mix of different chaos maps for a specific set of control settings. There is a complete explanation of how encryption and decryption operations work. The security analysis results showed that the suggested cryptosystem is safe from statistical, brute force, and differential attacks. Compared to already known methods, the estimated times for encryption and decryption make it likely that the proposed scheme can be applied in real-time applications.

A deep learning signed medical image based on cryptographic techniques

Innovative medical multimedia communications technology requirements have enhanced safety principles, allowing significant advancement in security standards. In hospitals and imaging centers, massive amounts of medical images have been created. To successfully access the medical databases and utilize those rich resources in assisting diagnosis and research, image processing enabled communication solutions are necessary. Our article presents a rigorous verified model by employing deep learning to enhance the cryptographic performance of biomedical images using hybrid chaotic Lorentz map diffusion and de-oxyribonucleic acid (DNA) confusion stages. It consists of two encryption/decryption techniques, the initial signal is verified using digital signature and two unique non-consecutive stages of chaotic diffusion with a single DNA scrambling stage in between. The encoded secret bit stream is generated and used to encrypt or decode the original signal in the diffusion manner to disintegrate the redundancy in the plain image statistics, utilizing hybrid chaotic system. Using DNA confusion step to make the relationship between the original signal and the utilized key more ambiguous. These stages make the proposed image cryptosystem more resistant to known/ chosen plaintext assaults. The performance of the suggested technique will be assessed to the most similar techniques reported in the literature for comparative purposes.

Speech Scrambling based on Particle Swarm Optimisation

Securing any communication system where important data may be transmitted through the channel is a very crucial issue. One of the good solutions in providing security for the speech is to use speech scrambling techniques. The chaotic system used in security has properties that make it a good choice for scrambling speech signal and the optimisation algorithm can provide a perfect performance when used to enhance the hybrid of more than one method. In this paper, we suggest a system that uses an optimisation method, namely, particle swarm optimisation. The evaluation measures prove that the output of the optimisation method has better performance among the methods used in the comparison, including chaotic maps and hybrid chaotic maps.

Asymmetric multiparameter encryption of hyperspectral images based on hybrid chaotic mapping and an equal modulus decomposition tree.

We present an asymmetric encryption scheme for hyperspectral images using hybrid chaotic maps (HCMs) and an equal modulus decomposition tree (EMDT) structure in a discrete multiple-parameter fractional Fourier transform (dmpFrFT) domain. The original hyperspectral image was scrambled by an HCM and then encrypted into asymmetric ciphertext using the EMDT. In the EMDT, each pair of the band images of the scrambled hyperspectral image were regarded as leaf nodes, while the encryption modules using chaotic random phase mask, dmpFrFT, and improved equal modulus decomposition were regarded as branch nodes, and the encryption process was implemented along the paths from the leaf nodes to the topmost branch node. The EMDT structure could provide multiparameter encryption, real-valued output, and different pairs of band images with different secret keys and encryption/decryption paths. Compared with the previous optical encryption approaches for hyperspectral images, our asymmetric cryptosystem had larger key space, less data amount of storage and transmission, and stronger resistance to statistical attacks. Various numerical simulations verified the performance of our proposed asymmetric cryptosystem.

An efficient color/grayscale image encryption scheme based on hybrid chaotic maps

Image encryption has become the essential way to secure image information with the high frequency of multimedia information exchange on the Internet. In this paper, an effective chaotic color/grayscale image encryption algorithm is proposed. The algorithm uses a hybrid 2D composite chaotic map combined with a sine–cosine cross-chaotic map for the transformation required to scramble the image as a confusion phase. As for the diffusion phase, a 1D combined Logistic-Tent chaotic map is used to generate a chaotic self-diffusion matrix that is bitwise XORed with the scrambled image to produce the final cipher image. The proposed algorithm combines the merits of both 1D and 2D chaotic maps; it has a simple structure, easy implementation, and excellent chaotic features making its chaotic orbits more unpredictable for introducing more security. The simulation and analysis results proved that the algorithm has a promising security performance and has a high ability to resist statistical and differential attacks.