Proposed Encryption Method Research Articles

Security and Privacy Protection for Online Electronic Documents Based on Novel Encryption Techniques

Corporate strategies have employed techniques that enter the domain of shadow and espionage in this rapidly developing, technologically competitive business environment. Supporting a security strategy is a way to counter these possible dangers. To preserve corporate success in the marketplace, network security needs to be crucial to the protection of electronic documents. Encryption technology has become more important in recent years for protecting online digital documents. This research was motivated by the fact that document verification has become quite time-consuming and difficult due to a variety of challenging and laborious processes. Existing technologies often malfunction when a single kind of encryption, such as AES, Data Encryption Standard (DES), or Rivest, Shamir, Adleman (RSA), is utilized at the request of the customer. Therefore, this study proposes hybrid cryptography, which integrates two novel algorithms into existing encryption protocols. A digital signature is generated for the data when a user uploads a data. The data are encrypted in parallel using the suggested Secured Hash Function-256 (SHA-256) method with improved DES and RSA (SHA-256+Enhanced DES+RSA). The proposed encryption method was shown to be more accurate than previous studies in experimental evaluations of data encryption.

Key dependent information confidentiality scheme based on deoxyribonucleic acid (DNA) and circular shifting

In this era of advanced information technology, the exploration and development of novel mechanisms to ensure information confidentiality have consistently captivated the attention of upcoming researchers. In this article, we present a pioneering approach that combines DNA sequencing with a four-dimensional (4D) hyperchaotic map to bolster the security of digital information. Our primary focus is on the design of a robust and secure scheme for encrypting color images, leveraging DNA cryptography and hyperchaos. By extracting three distinct DNA sequences, we generate encryption keys through the integration of DNA computing and 4D hyperchaotic maps. Notably, these keys are intricately linked to the plaintext and vary with any alterations in the input. Consequently, the proposed encryption method stands resilient against an array of potential cryptographic attacks. To gauge the algorithm's security, we subject it to rigorous standard statistical analysis. Our findings underscore the efficiency and robustness of the proposed framework, establishing its potential for facilitating secure communication.

Separable and reversible data hiding scheme for medical images using modified Logistic and interpolation

The interpolation technique (IT) is a fundamental tool for image processing and is commonly utilized. Various IT-based reversible data hiding (RDH) schemes for encrypted medical images have been proposed in recent years. However, these schemes have encountered issues such as simplistic encryption, low embedding rate, or incomplete separation. A high-capacity IT-based separable RDH scheme for medical images is proposed to address these issues. First, the original Logistic map is modified by adding extra parameters to increase the complexity of the key. Additionally, an encryption method via bit reorganization and diffusion is presented to encrypt the original image. Second, an improved interpolation method based on the neighbor pixel mean is proposed to interpolate the encrypted (ciphertext) image to generate a cover (interpolated) image for embedding the data. Finally, a new data embedding method is developed using the modulo-operation congruence theorem. Experimental results showed that the modified Logistic map exhibits excellent chaotic characteristics, the metrics of the proposed encryption method are close to the theoretical values, and the proposed data hiding method acquires high embedding capacity and image quality. Furthermore, the proposed scheme is a fully reversible and separable technique that achieves superior performance in comparison to various IT-based encrypted RDH schemes.

Integrated dual hyperchaotic and Josephus traversing based 3D confusion-diffusion pattern for image encryption

This paper introduces an enhanced image encryption technique that relies on 3D confusion and diffusion patterns, aiming to achieve maximum performance in terms of confusion and diffusion. The proposed encryption method combines four phases: dual hyperchaotic, improved logistic map (ILM), Josephus traversing, and a hash function. The first and second phases utilize improved Chen and Lorentz systems-based 3D patterns to enhance confusion and diffusion. In the third phase, bit-plane permutations are performed through Josephus traversing in three directions: x, y, and z. Lastly, the fourth phase implements diffusion based on ILM to optimize encryption performance. The integration of a hash function in this method serves to heighten key sensitivity. The test results demonstrate the method's exceptional performance across various analyses, including statistical, differential, brute-force, and NIST test suite assessments. Additionally, the proposed method outperforms previous approaches significantly, as indicated by the majority assessment.

A Robust and Secure Watermarking Approach Based on Hermite Transform and SVD-DCT

Currently, algorithms to embed watermarks into digital images are increasing exponentially, for example in image copyright protection. However, when a watermarking algorithm is applied, the preservation of the image’s quality is of utmost importance, for example in medical images, where improper embedding of the watermark could change the patient’s diagnosis. On the other hand, in digital images distributed over the Internet, the owner of the images must also be protected. In this work, an imperceptible, robust, secure, and hybrid watermarking algorithm is presented for copyright protection. It is based on the Hermite Transform (HT) and the Discrete Cosine Transform (DCT) as a spatial–frequency representation of a grayscale image. Besides, it uses a block-based strategy and a perfectibility analysis of the best embedding regions inspired by the Human Vision System (HVS), giving the imperceptibility of the watermark, and a Singular-Value Decomposition (SVD) approach improved robustness against attacks. In addition, the proposed method can embed two watermarks, a digital binary image (LOGO) and information about the owner and the technical data of the original image in text format (MetaData). To secure both watermarks, the proposed method uses the Jigsaw Transform (JST) and the Elementary Cellular Automaton (ECA) to encrypt the image LOGO and a random sequence generator and the XOR operation to encrypt the image MetaData. On the other hand, the proposed method was tested using a public dataset of 49 grayscale images to assess the effectiveness of the watermark embedding and extraction procedures. Furthermore, the proposed watermarking algorithm was evaluated under several processing and geometric algorithms to demonstrate its robustness to the majority, intentional or unintentional, attacks, and a comparison was made with several state-of-the-art techniques. The proposed method obtained average values of PSNR = 40.2051 dB, NCC = 0.9987, SSIM = 0.9999, and MSSIM = 0.9994 for the watermarked image. In the case of the extraction of the LOGO, the proposal gave MSE = 0, PSNR ≫ 60 dB, NCC = 1, SSIM = 1, and MSSIM = 1, whereas, for the image MetaData extracted, it gave BER = 0% and Berror=0. Finally, the proposed encryption method presented a large key space (K=1.2689×1089) for the LOGO image.

NEW APPROACH TO BOOK CIPHER: WEB PAGES AS A CRYPTOGRAPHIC KEY

Research relevance: Since ancient times, people have widely used methods of concealment and coding during information sharing, and ensuring the protection of information is currently relevant. Encryption methods are developing daily in order to ensure the reliable protection of confidential information and the exchange of data on the network. The subject and purpose of the research are to develop an encryption method, which is based on the ideology of book cipher and uses web pages as a cryptographic key, in the organization of a secure exchange of information. The following tasks are solved in the article: The article provides information about book cipher and analyzes modern methods of book cipher, as well as proposes a novel encryption method involving the use of web pages as a cryptographic key. Research methods: In the paper methods of analysis and synthesis are used. Obtained results and conclusions: The possibility of transforming the book cipher is proved, and a novel encryption method involving the use of web pages as a cryptographic key is proposed. The article also provides a comparison between the proposed encryption method involving the use of Internet pages as a cryptographic key with the classic book cipher method.

Security and storage improvement in distributed cloud data centers by increasing reliability based on particle swarm optimization and artificial immune system algorithms

SummaryOne of the major concerns in security and storage improvement of data centers is due to the fact that there is a possibility of access to cloud information, and the distance between data centers for data transfer causes cloud storage problems. In this article, an encryption method using artificial immune system (AIS) is leveraged to secure sensitive data in data centers and particle swarm optimization (PSO) algorithm is exploited to improve the selection of storage services in distributed cloud data centers to store and transfer particular a data set between data centers. To obtain satisfied performance considering the transmitting cost, and smallest transmitting distance, we exploited one discrete PSO algorithm and AIS method and called PSO_AIS. To evaluate the proposed PSO_AIS algorithm, we designed the experiments and simulated it in MATLAB software. In the simulation, we conducted experiments on 13 data centers located in different locations in Iran. The experimental results expose that the proposed algorithm reduces 30% the distance and cost to select a particular data center for a particular data set. Experiments have been carried‐out to demonstrate the effectiveness of the proposed encryption method, which is based on AIS. The results showed that the encoding performance of the proposed method is better than other methods.

An Efficient Color-Image Encryption Method Using DNA Sequence and Chaos Cipher

Nowadays, high-resolution images pose several challenges in the context of image encryption. The encryption of huge images’ file sizes requires high computational resources. Traditional encryption techniques like, Data Encryption Standard (DES), and Advanced Encryption Standard (AES) are not only inefficient, but also less secure. Due to characteristics of chaos theory, such as periodicity, sensitivity to initial conditions and control parameters, and unpredictability. Hence, the characteristics of deoxyribonucleic acid (DNA), such as vast parallelism and large storage capacity, make it a promising field. This paper presents an efficient color image encryption method utilizing DNA encoding with two types of hyper-chaotic maps. The proposed encryption method comprises three steps. The first step initializes the conditions for generating Lorenz and Rossler hyper-chaotic maps using a plain image Secure Hash Algorithm (SHA-256/384). The second step performs a confusion procedure by scrambling the three components of the image (red, green, and blue) using Lorenz hyper-chaotic sequences. Finally, the third step combines three approaches to encrypt the scrambled components for diffusion: DNA encoding/decoding, addition operation between components, and XORing with Rossler hyper-chaotic sequences. The simulation results indicate that the suggested encryption algorithm satisfies the requirements of security. The entropy value of confusion and diffusion is 7.997, the key space is 2²⁰⁰, and the correlation coefficient is nearly zero. The efficacy of the proposed method has been verified through numerous evaluations, and the results show its resistance and effectiveness against several attacks, like statistical and brute-force attacks. Finally, the devised algorithm vanquishes other relevant color image encryption algorithms.

Applicable Image Security Based on Computational Genetic Approach and Self-Adaptive Substitution

With the emergence of new information technology fields and various usages of internet applications, securing massive amounts and multiple varieties of multimedia data has become a significant challenge. Hence, it is essential to investigate and develop new cryptographic algorithms to ensure the protection and privacy of multimedia data at rest and during transmission through the communication channel while attempting to overcome the limitations of traditional cryptographic methods. This paper suggests a novel image encryption and decryption technique based on a computational genetic approach and self-adaptive chaotic substitution. The proposed encryption method depends mainly on four steps: sequence generation, diffusion, confusion, and optimization. The USC-SIPI image dataset is being utilized to prove the correctness and effectiveness of our approach in defending against different attack types. Furthermore, the proposed technique could be capable of withstanding attacks while achieving an information entropy of 7. 999, Number of Pixel Change Rate of 99.62%, and a Unified Average Change in Intensity of 33.54%, respectively. The results of security testing and analysis revealed that our image security method is strongly recommended for modern communications security applications.

Method of encrypting images based on two multidimensional chaotic systems using fuzzy logic

The subject of the study: it is proposed to develop a method of image encryption with pixel permutation implemented using fuzzy logic and Hainaut mapping, as well as diffusion, which is implemented using the Lorenz system. Study objectives: To propose an effective way to apply the rules of fuzzy logic in relation to the values generated by the Henon mapping to implement the permutation of pixels in the image, which will provide a random permutation and increase the efficiency of the encryption method. Also, to achieve better security in the process of image encryption, the use of the diffusion process implemented using the Lorenz system. In addition, to increase the sensitivity of the encryption method to change the initial value of the component colors of the pixels will also be used in the encryption process. Investigation methods and research results: developed and presented a method of image encryption with pixel permutation implemented using fuzzy logic and Henon mapping, as well as diffusion, implemented using the Lorenz system. The initial values for the Henon mapping and the Lorenz system will be determined from the entered keyword, and the control parameters are set by the operator, while the values of the component colors of the pixels will also participate in the encryption process. In addition, before the process of rearranging the pixels in the image, the rules of fuzzy logic are implemented by Henon mapping. Also, the values of the component pixels before and after the diffusion procedure will be reduced to a single interval. Thus, as a result of image encryption, the original image changes completely, loses its content and shape, and the color intensity distribution of pixels becomes uniform. The program implementation of the proposed encryption method was also carried out and the qualitative characteristics of the proposed image encryption method were evaluated, namely: analysis of histograms of original and encrypted images, correlation of adjacent image pixels, root mean square error (MSE), peak signal-to-noise ratio (PSNR), entropy before changing the color components of the pixels. Conclusions: the implementation of the method has shown that it has a large number of encryption keys, which makes brute force (the process of their selection) resource-intensive and complex, and the implementation of the encryption process in two stages and using two different chaotic systems significantly improves the security of the encrypted image. The resulting cryptosystem is also resistant to the following attacks: approximation of chaotic orbits, correlation, analytical and statistical attacks.

A Novel Chaos-Based Privacy-Preserving Deep Learning Model for Cancer Diagnosis

Early cancer identification is regarded as a challenging problem in cancer prevention for the healthcare community. In addition, ensuring privacy-preserving healthcare data becomes more difficult with the growing demand for sharing these data. This study proposes a novel privacy-preserving non-invasive cancer detection method using Deep Learning (DL). Initially, the clinical data is collected over the Internet via wireless channels for diagnostic purposes. It is paramount to secure personal clinical data against eavesdropping by unauthorized users that may exploit it for personalized interests. Therefore, the collected data is encrypted before transmission over the channel to prevent data theft. Various security measures, including correlation, entropy, contrast, structural content, and energy, are used to assess the proposed encryption method's efficiency. In this paper, we proposed using the Convolutional Neural Network (CNN)-based model and Magnetic Resonance Imaging (MRI) with different techniques, including transfer learning, fine-tuning, and K-fold analysis cancer detection. Extensive experiments are carried out to evaluate the performance of the proposed DL techniques with regard to traditional machine learning approaches such as Decision Tree (DT), Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM). Results show that the CNN-based model has achieved an accuracy of 98.9% and outperforms conventional ML algorithms. Further experiments demonstrate the efficiency of both encryption schemes, achieving entropy, contrast, and energy of 7.9999, 10.9687, and 0.0151, respectively.

A Novel Separable Scheme for Encryption and Reversible Data Hiding

With the increasing emphasis on security and privacy, video in the cloud sometimes needs to be stored and processed in an encrypted format. To facilitate the indexing and tampering detection of encrypted videos, data hiding is performed in encrypted videos. This paper proposes a novel separable scheme for encryption and reversible data hiding. In terms of encryption method, intra-prediction mode and motion vector difference are encrypted by XOR encryption, and quantized discrete cosine transform block is permutated based on logistic chaotic mapping. In terms of the reversible data hiding algorithm, difference expansion is applied in encrypted video for the first time in this paper. The encryption method and the data hiding algorithm are separable, and the embedded information can be accurately extracted in both encrypted video bitstream and decrypted video bitstream. The experimental results show that the proposed encryption method can resist sketch attack and has higher security than other schemes, keeping the bit rate unchanged. The embedding algorithm used in the proposed scheme can provide higher capacity in the video with lower quantization parameter and good visual quality of the labeled decrypted video, maintaining low bit rate variation. The video encryption and the reversible data hiding are separable and the scheme can be applied in more scenarios.

A secure telemedicine electronic platform based on lightweight cryptographic approach

Telemedicine platforms have emerged as one of the most harnessed studies in recent years, especially after the spread of pandemics. Due to the epidemic, telemedicine distribution to rural or isolated areas has become an urgent need. However, there are several obstacles to providing remote medical care, the most significant of which is protecting patient data while sustaining the speed of communication between the patient and the medical staff. The significant of this study is to provides a lightweight encryption/decryption technique that uses on the internet of medical things in stance of bio-sensors and bio-actuators. This study is one of the cybersecurity approaches, such type of encryption has little effect on the speed of data transmission. The Diffie Hellman technique is used as a lightweight encryption method because it includes four encryption-keys. The efficiency of the proposed encryption method has been compared with several equivalent methods. According to experimental results, the proposed encryption method represents a lightweight and secure method which can accomplish the level of protection that required to secure medical information despite the data’s disarray.

A Proposed Method for Achieving the Confidentiality of Arabic Texts

Due to the rapid development of distributed computing systems, the use of local networks, and the huge expansion of the Internet, the process of maintaining the confidentiality of information becomes important and necessary. Encryption is one of the most important ways to keep information confidential and to prevent unauthorized people from disclosing this information. Many cryptographic algorithms have appeared in different ways and methods. But most of these algorithms have been devoted for encrypting texts in the English language. Because of the increasing important and sensitive information exchange in the Arabic language by users on the Internet, an urgent need has appeared to build dedicated encryption systems for the Arabic language. The aim of this research is to provide a proposed encryption method that uses the idea of combining the methods of transposition and substitution cipher for the purpose of Arabic texts confidentiality. This research depends on using diacritics in the Arabic language to perform the process of substitution cipher. The efficiency of the proposed method has been tested on different texts; the method provides high speed execution, the length of the encrypted texts is almost close to the clear text length, and the confidentiality of the resulting encrypted texts is high.

A novel and efficacious use of three-dimensional intertwining logistic map for the security of greyscale images

ABSTRACT A chaos-based security algorithm for images using symmetric keys is presented in this work. The chaotic 3D intertwining logistic map (ILM) is employed in a compact and efficacious way in the proposed work. The three chaotic sequences generated by the 3D ILM are utilized in an effective way to confuse and diffuse the original image and form an encrypted image. The dependency of initial key values and the controlling parameters of the 3D ILM on the plain image and 128-bit key stream are promising features. These features significantly increase the security of the proposed encryption method. The simulation outcomes and comparative findings with the existing schemes are favourable and satisfactory, thus support the performance and reliability of the suggested encryption system. In addition, the advantageous and acceptable results of theoretical value tests, key sensitivity results and high key space help to counter different kinds of attacks such as statistical, differential and exhaustive attacks.

Noninvasive Detection of Respiratory Disorder Due to COVID-19 at the Early Stages in Saudi Arabia

The Kingdom of Saudi Arabia has suffered from COVID-19 disease as part of the global pandemic due to severe acute respiratory syndrome coronavirus 2. The economy of Saudi Arabia also suffered a heavy impact. Several measures were taken to help mitigate its impact and stimulate the economy. In this context, we present a safe and secure WiFi-sensing-based COVID-19 monitoring system exploiting commercially available low-cost wireless devices that can be deployed in different indoor settings within Saudi Arabia. We extracted different activities of daily living and respiratory rates from ubiquitous WiFi signals in terms of channel state information (CSI) and secured them from unauthorized access through permutation and diffusion with multiple substitution boxes using chaos theory. The experiments were performed on healthy participants. We used the variances of the amplitude information of the CSI data and evaluated their security using several security parameters such as the correlation coefficient, mean-squared error (MSE), peak-signal-to-noise ratio (PSNR), entropy, number of pixel change rate (NPCR), and unified average change intensity (UACI). These security metrics, for example, lower correlation and higher entropy, indicate stronger security of the proposed encryption method. Moreover, the NPCR and UACI values were higher than 99% and 30, respectively, which also confirmed the security strength of the encrypted information.

A Multi-Image Encryption Based on Sinusoidal Coding Frequency Multiplexing and Deep Learning.

Multi-image encryption technology is a vital branch of optical encryption technology. The traditional encryption method can only encrypt a small number of images, which greatly restricts its application in practice. In this paper, a new multi-image encryption method based on sinusoidal stripe coding frequency multiplexing and deep learning is proposed to realize the encryption of a greater number of images. In the process of encryption, several images are grouped, and each image in each group is first encoded with a random matrix and then modulated with a specific sinusoidal stripe; therefore, the dominant frequency of each group of images can be separated in the Fourier frequency domain. Each group is superimposed and scrambled to generate the final ciphertext. In the process of decryption, deep learning is used to improve the quality of decrypted image and the decryption speed. Specifically, the obtained ciphertext can be sent into the trained neural network and then the plaintext image can be reconstructed directly. Experimental analysis shows that when 32 images are encrypted, the CC of the decrypted result can reach more than 0.99. The efficiency of the proposed encryption method is proved in terms of histogram analysis, adjacent pixels correlation analysis, anti-noise attack analysis and resistance to occlusion attacks analysis. The encryption method has the advantages of large amount of information, good robustness and fast decryption speed.

Invertible encryption network for optical image cryptosystem

In this paper, an invertible encryption network (IENet) is firstly proposed for optical image cryptosystem, which applies a novel learning way to optical image encryption for the first time, to the best of our knowledge. Here, the quadratic phase and double phase method are firstly applied to generate the phase-only hologram, and then it is encrypted by IENet. The ciphertext is finally obtained by learning the probability distribution from the most uniform matrix with an entropy of 8.0. Notably, the decryption process is the inverse process of the encryption. Due to the invulnerability of the ciphertext-only attack, chosen-ciphertext attack, and cryptosystem leakage, a high security is achieved by the proposed encryption method. Moreover, the optical video decryption is accomplished by combining optics and deep learning owing to the fast decryption of the neural network. The effectiveness and superiority of the proposed encryption method is verified by the simulation and experiment results. The proposed method provides a new approach and perspective for the learning-based encryption research.

Color Image Encryption Using Angular Graph Fourier Transform

In this paper, an angular graph Fourier transform (AGFT) is introduced to encrypt color images with their intrinsic structures. The graph Fourier transform (GFT) is extended to the AGFT and proven to have the desired properties of angular transform and graph transform. In the proposed encryption method, color images are encoded by DNA sequences and confused under the control of chaotic key streams firstly. Secondly, sparse decomposition based on the random walk is applied to scramble pixels spatially, and a series of sub-images are obtained. This step increases encryption efficiency. Finally, the intrinsic sub-image structure is reflected by graphs, and the signals on different subgraphs are transformed into different AGFT domains with particular angular parameters, which makes the proposed method relevant to the original image structure and enhances security. The experimental results demonstrate that the proposed algorithm can resist various potential attacks and achieve better performance than the state-of-the-art algorithms.

Wireless COVID-19 Telehealth: Leukocytes Encryption Guided by Amino Acid Matrix.

In this era of wireless COVID-19 telehealth, visiting hospital for regular follow-ups could invite coronavirus in someone’s body. Opting for proactive E-health services is the best thing. It helps the remote patients to share their confidential data through secured encryption. Telehealth services are emerging element in these proactive medical sciences. It helps the remote patients to share their confidential data through secured transmission. In this paper, amino acid guided matrix encoding scheme has been proposed. White blood cell count or Leukocute count is a dominant indicator of patients’ health condition, even amid COVID-19. An abnormal growth in leukocyte count is mainly caused due to an infection, cancer, or any other severe symptoms. It initiates internal haematological inflammations, cardiovascular diseases, Type II diabetes, etc. Therefore, tracking leukocyte count may for disease diagnosis and further treatments. The leukocyte count is generally done in different pathologies, and the data evaluation needs the expertise of a pathologist. In this paper, a technique involving security measures to transmit the result of the histological test with the help of cryptography has been proposed. The data to be transferred to the concerned physician for further diagnosis with the help of proposed way of encryption using amino acids, which ensures no data loss, no data modification, no data theft in the middle of transmission. The proposed encryption method using the amino acid codes has produced results showing satisfactory performances such as p-values found to be 7.215544e−04 and 8.48904e−03 for the key stream and cipher key matrix monobit test respectively, and 8.10245e−04 and 8.10245e−04 for the key stream and cipher key matrix frequency test respectively. It may be used as a transmission module in any wireless COVID-19 Telehealth Systems.