Security Of Image Data Research Articles

An efficient hybrid chaotic map-based encryption technique for multiple image security systems

Researchers are increasingly interested in image encryption in the modern technological era. Their goal is to improve the security of image data from unauthorized sources. Due to its randomness and unpredictable behavior, chaos theory is considered the most suitable method for encrypting images. An image encryption algorithm based on diffusion maps is presented in this paper. An element of nonlinearity is generated by modifying the pixel values with a chaotic map first. Three chaotic maps are used in the proposed image encryption scheme. In an efficient encryption algorithm based on the improved three chaotic maps, the permuted image is subjected to a diffusion process using the key from the original image. This scheme has the advantage of a large key space and is resistant to various attacks. Real-time applications are suitable for the proposed scheme because of their high-security level and low computational complexity.

Chaotic Quantum Encryption to Secure Image Data in Post Quantum Consumer Technology

Chaotic Quantum Encryption to Secure Image Data in Post Quantum Consumer Technology

Efficient and privacy-preserving image classification using homomorphic encryption and chunk-based convolutional neural network

Image feature categorization has emerged as a crucial component in many domains, including computer vision, machine learning, and biometrics, in the dynamic environment of big data and cloud computing. It is extremely difficult to guarantee image data security, privacy, and computing efficiency while also lowering storage and transmission costs. This paper introduces a novel method for classifying image features that combines multilevel homomorphic encryption and image data partitioning in an integrated manner. We employ a novel partitioning strategy to reduce computational complexity, significantly reducing computational load and improving classification accuracy. In the quest for increased data security and privacy, we introduce a novel, fully homomorphic encryption approach specialized to partitioned images. To counter the inherent complexity of encryption, we devise a compound encryption strategy that exploits the full potential of homomorphic computation, with an explicit objective to curtail computational and storage overheads. Evidently superior to conventional methods, our methodology showcases pronounced benefits in computational efficiency, storage and transmission cost reduction, and robust security and privacy preservation. Hence, the methodology put forth in this paper presents a pioneering and efficacious resolution to the multifaceted challenges of image feature classification within the intricate milieu of cloud computing and big data.

A Password and Least Significant Bit Substitution Based Steganography Technique for Image Hiding

The proposed work introduces an image steganography technique using text-based password that acts as the symmetric key of encryption and decryption. It contains two components, an encoder, and a decoder. An encoder takes a secret image that needs to be hidden inside another cover image. The Combined image is encrypted with an eight characters’ password. The starting position of the cover image from where the secret image starts to hide depends on the password. Then the (Least Significant Bit) LSB Substitution technique is used to hide the entire secret image inside the cover image. The decoder takes the encrypted image and the password to retrieve the secret image back. The proposed work produces an encrypted image by keeping 99% information of the cover image and 100% information of the secret image, thus it provides lossless retrieval of the secret image. The proposed work includes dynamicity of position in steganography that ensures more security of image data over the network than the existing state of art methods.

Secure transmission of grayscale images with triggered error visual sharing

<p>In the digital era, data transfer plays a crucial role in various industries such as banking, healthcare, marketing, and social media. Images are widely used as a means of communication. The presence of cyber attackers poses a significant risk to data integrity and security during transmission. According to the cost of data breach report 2021, the healthcare industry has experienced the highest costs associated with data breaches, highlighting the need for robust security measures. Visual cryptography (VC) is a technique used to secure image data during transmission. It involves encrypting the image and dividing it into shares, which are then communicated to the intended recipients. Each individual share does not reveal any classified information. At the destination, the shares are digitally combined to reconstruct the original image. When implementing VC, several factors need to be considered, including security, computational complexity, and the quality of the reconstructed image. In this paper, a new method called progressive meaningful visual cryptography (PMVC) is proposed for transferring secret images. The PMVC method introduces an error instance that triggers meaningful shares generation. The proposed method ensures the quality of the reconstructed image by achieving a peak signal-to-noise ratio (PSNR) of up to 37 dB.</p>

Increasing embedding capacity of stego images by exploiting edge pixels in prediction error space

In the field of data concealing, edge detection techniques are frequently employed, particularly for improving image quality and data security. These methods, however, have a lower embedding capacity. In order to take advantage of more edge pixels, many strategies are used nowadays. These schemes either combine the output from multiple edge detectors or enlarge the edges of an edge image by dilating. Even so, if the amount of data is vast, the techniques might not be able to conceal all of it. Therefore, a novel strategy for edge exploitation is still needed to regulate the effectiveness of edge detection-based data-hiding strategies. By using edge detectors in the prediction error space, we utilized more edge pixels in this study (PES). Applying a predictor on the cover image and then calculating the prediction errors, we prepared the PES. The edges in PES were then marked using the edge detector. The edge-error corresponding pixels received more information than the relevant pixels that did not create an edge-error. Additionally, we combined the results from different edge detectors to produce more edges, which does help to achieve a higher embedding capacity. We implanted x number of secret bits in edge pixels and y number of bits in non-edge pixels where x>y. The simulation results show that the proposed scheme outperforms its rivals on all performance-measuring criteria, including payload, stego image quality, and resistance to attack.

Duple Color Image Encryption System Based on 3-D Nonequilateral Arnold Transform for IIoT

The Industrial Internet of Things (IIoT) is to continuously integrate network communication, intelligent analysis and other technologies into every link of the industrial production process, thus greatly improving the manufacturing efficiency. While such systems greatly improve the productivity of the industry, they introduce major safety challenges during the design and operational phases. Therefore, it is necessary to encrypt and protect the information transmitted by the system during the design and runtime stages. This paper focuses on the transmission security of image data in every link of IIoT. Two color images that need to be transmitted can be encrypted into color ciphertext image by using 3D Non-equilateral Arnold Transform (3D-NEAT) and 3D Lorenz System (3D-LS). Different from the traditional algorithm which encrypts one plain image into one ciphertext image, our algorithm encrypts two color images into one color ciphertext image which will cause great confusion to the attacker whom illegally breaks the ciphertext image. First, the proposed method converts two color images with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N\times M$</tex-math></inline-formula> into a 3D bit-level matrix with size <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N\times M\times 48$</tex-math></inline-formula> . Next, 3D-NEAT is applied to permutate the positions of the elements of the resulted 3D bit-level matrix. Then, the permutated 3D bit-level matrix is transformed into three 2D pixel-level images and then diffused by the random diffusion sequences which 3D-LS generates. Finally, the scrambling matrices generated by 3D-LS are used to scramble three diffused 2D pixel-level images and the output is considered as three color components of the encrypted image. The numerical experiments and security analysis show that the proposed image encryption scheme has strong resistance to several known attacks, and yields near-zero correlation and near-eight entropy for the RGB cipher image, and some performance is better than some of the recently proposed image encryption 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

Advances in medical image watermarking: a state of the art review.

Watermarking has been considered to be a potent and persuasive gizmo for its application in healthcare setups that work online, especially in the current COVID-19 scenario. The security and protection of medical image data from various manipulations that take place over the internet is a topic of concern that needs to be addressed. A detailed review of security and privacy protection using watermarking has been presented in this paper. Watermarking of medical images helps in the protection of image content, authentication of Electronic Patient Record (EPR), and integrity verification. At first, we discuss the various prerequisites of medical image watermarking systems, followed by the classification of Medical Image Watermarking Techniques (MIWT) that include state-of-the-art. We have classified MIWT's into four broader classes for providing better understanding of medical image watermarking. The existing schemes have been presented along with their cons so that the reader may be able to grasp the shortcomings of the technique in order to develop novel techniques proving the inevitability of the presented review. Further, various evaluation parameters along with potential challenges pertaining to medical image watermarking systems have been discussed to provide a deep insight into this research area.

A Secure and Efficient Cryptography System Based on Chaotic Maps for Securing Data Image in Fog Computing

The huge availability and prosperity of net technology results in raised on-line media sharing over the cloud platform which has become one of the important resources and tools for development in our societies. So, in the epoch of enormous data great amount of sensitive information and transmission of different media transmitted over the net for communication. And recently, fog computing has captured the world's attention due to their inherent features relevant compared to the cloud domain, But this push to head for many issues related to data security and privacy in fog computing which it's still under studied in their initial juncture. Therefore, in this paper, we will review a security system that relies on encryption as a kind of effective solution to secure image data. We use an approach of using chaotic map plus space curve techniques moreover the confusion and diffusion strategies are carried out utilizing Hilbert curvature and chaotic map such as two-dimensional Henon map (2D-HM) to assert image confusion with pixel level permutation .Also we relied in our system the way of shuffling the image with blocks and use a key for each block, which is chooses randomly to have a high degree of security. The efficiency of the proposed technique has been tested utilizing different investigations like analysis of entropy [7.9993], NPCR [99.6908%] and finally UACI [33.6247%]. Analysis of results revealed that the proposed system of image encryption technique has favorable effects, and can achieve a good results moreover it fights different attacks and by comparing with another techniques denote that our proposed fulfills high security level with high quality.

Image Encryption Using Dynamic Image as a Key Based on Multilayers of Chaotic Permutation

With the rapid expansion of electronic data transmission, unauthorized data access is growing. Information security against unwanted access is becoming increasingly essential in data storage and data transfer. Images are a common type of information that is used in almost every aspect of life, so the security of image data against unwanted access is critical. In this article, we propose an encryption technique that uses a symmetric encryption method based on XOR operation between the plain image and another image that will be used as a key agreed upon by both the sender and recipient. To ensure the security of the plain images, the scheme performs pixel permutation procedures dynamically using random numbers on the key image and plain image in each encryption process, which renders the encryption algorithm strong and brute-force resistant. Simulation results on several standard images showed a random distribution of pixel values and a higher pass rate correlated with entropy and ideal values for analysis parameters. Thus, through the use of randomization, the proposed algorithm is resistant to various attacks and offers promising security measurements while maintaining efficient and fast execution.

Ownership protection system for partial areas on image data using ethereum blockchain

Our proposed method utilizes blockchain technology to safeguard the ownership of specific regions within image data. In our approach, diverse values could be assigned to each region based on its importance, and only users with ownership rights can access these designated regions. This ensures the protection of ownership rights for individuals in any given region of an image. Identified regions are individually encrypted using an XOR cipher, and a corresponding key image is generated for decryption, thereby preserving the privacy of the encrypted region. Non-fungible tokens (NFTs) are employed to protect the key image and manage the ownership of each object in the image data. The NFT for the key image is generated by the key holder (who possesses the entire image), and the ownership NFT is acquired by the user who needs access to the key NFT. Furthermore, the ownership NFT and the key NFT are verified for a match by the judgment function, and only upon successful validation, the NFT is displayed on the screen. This method enables different values to be assigned to various parts of an image, facilitating the transfer and sharing of ownership. Additionally, the original image?s owner can benefit financially based on the value of the image, thus enhancing the overall security of image data.

File Encryption Application using Menezes-Vanstone Elliptic Curve Cryptography Based on Python

Humans have been affected by the advent of information technology in many different ways. Information can be sent freely as a result of the conveniences offered. However, unauthorized parties may take advantage of this to retrieve and utilize the information without the owner's consent. In this paper, the authors perform text, image, audio, and video data security using a modified version of the Menezes-Vanstone elliptic curve cryptography algorithm. The study implements Menezes-Vanstone Elliptic Curve Cryptography in a program for file text, image, audio, and video encryption and decryption, while also providing performance data for both our program and alternative approaches for comparison. The outcome demonstrates that the encrypted file size is smaller than alternative approaches. Nevertheless, our program might benefit from some enhancements in terms of encryption and decryption times.

Retracted: Image Data Security Mechanism Based on the Internet of Things Cardiac Catheterization Laboratory Information Management System Research and Design.

[This retracts the article DOI: 10.1155/2021/5592185.].

Privacy Preservation Modelling for Securing Image Data using Novel Ethereum-based Ecosystem

The broad usage of images in real-time applications demands a cloud infrastructure due to its advantages. Many use cases are built where the image data is shared, sharing becomes the core function, and the medical domain takes its broad advantage. The cloud is a centralized infrastructure for its all-operation usages; it depends mainly on the trusted third party to handle security concerns. Therefore, the privacy preservation of the image data or any data becomes an issue of concern. The distrusted system advantages are achieved using blockchain technology for image data security and privacy concerns. The traditional approaches of the security and privacy models raise many apprehensions as these are designed on the centralized systems of the data sharing mechanisms. It is also observed that large data files are not wisely handled, which demands building a framework model that takes image data and any other data of any size to ensure a dependable optimal security system. This paper presents a framework model to achieve optimal time complexity for securing the privacy aspects of the image data or any other data that uses space optimal file system using distributed security mechanism for both the storage and sharing of the data. The proposed framework model for optimal time complexity and security uses a duplication algorithm using stakeholder agreement to ensure efficient access control to the resources using the cryptographic approach to the Ethereum ecosystem. The performance metric used in the model evaluation includes the degree of availability and efficiency. On benchmarks, it performs well compared to the traditional cloud-built distributed systems. The quantified outcome of the proposed scheme exhibits a 42.5% of reduction in time for data repositioning, a 41.1% of reduction in time for data retrieval, a 34.8% of reduction in operational cost, a 73.9% of reduction in delay, and a 61% faster algorithm execution time in contrast to conventional blockchain method.

BIOMEDICAL IMAGE AUGMENTATION AND TRANSMISSION USING STEGANOGRAPHY

Objective: The aim of the study was to embed sensitive patient information and image data in a cover image to enable secure transmission of confidential data. Methods: Image steganography is a process used to embed (hide with encryption) data which includes text, images or audio, and video files inside the main image file. This embedding is done by altering the values of some pixels which are chosen by the encryption algorithm. The algorithm used in this case is the Discrete Wavelet Transformation Algorithm using MATLAB. Results: Statistical features such as signal to noise ratio (SNR), Peak SNR, and (mean squared error) were extracted from the medical images to test the loss during steganography and transmission. Conclusion: A technique that enables secure and swift image data transmission using image steganography technique is proposed.

Enhancing Security of Medical Image Data in the Cloud Using Machine Learning Technique

Enhancing Security of Medical Image Data in the Cloud Using Machine Learning Technique

Secret image encryption based on chaotic system and elliptic curve cryptography

The advent of internet has been a boon to society. It has helped in information retrieval and is a great help in communication. Nowadays, communication comprises digital information in images, videos, GIFs, and many other formats. Amongst the digital data, images are one of the most transmitted data. Therefore, the security of image data has gained the attention of researchers. This paper addresses the drawbacks of Abdelfatah's method, a block-based image encryption scheme based on a chaotic system and elliptic curve cryptography. One of the issues is caused when multiple pixels are grouped to form large integers, which turns out to be more than the modulo prime of the elliptic curve leading to incorrect decryption. Another issue is to transfer extra information for the number of pixels that are grouped. In order to overcome, an algorithm is proposed that uses the largest 512 bits elliptic curve prime modulo along with confusion and diffusion operation using a chaotic system. Security and statistical analysis are conducted to substantiate the strength of the proposed enciphering method.

An Efficient Diffusion Approach for Chaos-Based Image Encryption and DNA Sequences

Experts and researchers in the field of information security have placed a high value on the security of image data in the last few years. They have presented several image encryption techniques that are more secure. To increase the security level of image encryption algorithms, this article offers an efficient diffusion approach for image encryption methods based on one-dimensional Logistic, three-dimensional Lorenz, DNA encoding and computing, and SHA-256. The encryption test demonstrates that the method has great security and reliability. This article, also, examines the security of encryption methods, such as secret key space analysis, key sensitivity test, histogram analysis, information entropy process, correlation examination, and differential attack. When the image encryption method described in this article is compared to several previous image encryption techniques, the encryption algorithm has higher information entropy and a lower correlation coefficient.

Data hiding to the image with bit plane slicing and double XOR

Data hiding is done in different environments and with different techniques, and applications in this area attract a lot of attention. In data hiding, the method of securing the data in the image by hiding data is one of the steganography methods. Bit Plane Slicing, one of the techniques applied in image steganography, is a reliable technique applied on images such as data hiding or compression, which allows us to operate on some special bits by separating each pixel that makes up the image into planes. This technique is aimed to provide high image quality and data security. In this study, two encryption layers and a concealment stage are proposed. Here, the bit planes of the three channels of the color image were first extracted using the BPS technique. The message to be hidden later was encrypted using a double XOR operation using binary representation and a secret key (extracted from the MSB). Then, the stream of encrypted bits is hidden in the cover image using the least significant bit plane. Well-known evaluation criteria such as MSE, PSNR, and histogram distribution were calculated to ensure the quality of the proposed method. Experimental results show that the proposed method has acceptable results and maintains the security of confidential text messages.