Image Data Encryption Research Articles

Chaos based image encryption scheme to secure sensitive multimedia content in cloud storage

Cloud computing offers a variety of on-demand services to users and has gained significant prominence in the contemporary era. The security of information stored in cloud data centers has become a central concern, especially for sensitive data like medical images, videos, and multimedia content that require heightened protection when stored in data centers. Cloud users have a responsibility to ensure the security of their data through strategic measures. Focusing on maintaining the privacy of images stored in the cloud, this research introduces an innovative image encryption technique that is based on a modified Skew Tent chaotic map. The suggested modification to the chaotic map includes combining the Skew Tent map with both the sine trigonometric function and perturbation technology. This results in enhanced randomness, more intricate dynamical behavior, a broader chaotic range, and increased sensitivity to initial values in contrast to alternative chaotic maps. The incorporation of this adapted map into a stepwise procedure, involving two rounds of permutation followed by diffusion, effectively accomplishes image data encryption for cloud storage systems. These consecutive operations collectively enhance the encryption method’s randomness and robustness. Through simulations conducted using Cloudsim, the cipher-image exhibits a uniform distribution and achieves a commendable information entropy score of 7.996749. The encryption algorithm significantly reduces correlation coefficients from 1 in the original image to 0 in the encrypted image, while maintaining NPCR (Number of Pixel Change Rate) and UACI (Unified Average Changing Intensity) values within the critical range. Additionally, both theoretical analysis and practical evaluations confirm the algorithm’s resilience against exhaustive, occlusion, and classical attacks. Moreover, extending this encryption framework to video data, a novel video encryption approach is proposed.

An approach for encrypting images using a four-dimensional logistic map

Encrypting image transmission has been one of the most complex challenges with communication technology ever. Millions of people utilize and share photographs via the internet for personal and professional purposes. One approach to secure picture transfer over the network is to use encryption techniques to transform the original picture into an unreadable or garbled version. Several novel and encouraging possibilities for creating secure Image data encryption techniques are presented by cryptographic algorithms grounded in chaotic logistic theory. Developing a foolproof method for encrypting both black-and-white and color image is the primary focus of this work. Both grayscale and color images can be encrypted using the keys generated by combining the chaotic logistic with the image's density in the first stage of the proposed system's encryption process. The original image can then be recovered in the second stage, which is the inverse of the encryption process. Two publicly available standard grayscale and color photographs were analyzed to evaluate the suggested approach. Peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), and number of pixels change rate (NPCR) were found to be 6.6268, 51.3011, and 100, respectively, according to the test findings.

JPEG-compatible Joint Image Compression and Encryption Algorithm with File Size Preservation

Joint image compression and encryption algorithms are intensively investigated due to their powerful capability of simultaneous image data compression and sensitive information protection. Unfortunately, most of the existing algorithms suffered from either poor compression efficiency or weak encryption strength, making them vulnerable to cryptanalysis. To address these limitations, we propose a chaos-based JPEG-compatible joint image compression and encryption algorithm. We separate the luminance and chrominance coefficients to preserve file size and encrypt the discrete cosine transform (DCT) coefficients in parallel. The proposed inter-block DC encryption strategy achieves high encryption intensity based on the permutation-substitution structure. In addition, we apply both inter- and intra-block permutations to AC coefficients and strengthen the encryption using an inter-block substitution for non-zero AC coefficients. The results of security and performance analyses demonstrate that the proposed algorithm offers robust encryption of image data while maintaining compression efficiency for real-time transmission.

A scheme for encrypted image data compression

A hybrid approach of image encryption and compression can give highly secured and compressed image data which can be easily transmitted through unsecured and bandwidth constrained channels. This paper proposes a mechanism which handles image encryption prior to image compression. The work is basically divided into two parts. The first part focuses on image encryption approach in which Roman numeral logic and pixel scrambling logic is applied to image data. The second part focuses on compression of encrypted image data using Huffman’s encoding. The proposed approach is lightweight, easy to understand and implement. Results are obtained using standard dataset and it is observed that 16%-18% compression is obtained after encryption.

A Secure IoT-Enabled Machine Learning Framework for Brain Tumor Classification and Prediction Using MR Image Data

Brain tumor identification and classification have improved due to the quick development of medical imaging and machine learning technology. This paper presents two approaches to secure image transmission in the Internet of Things (IoT): a comprehensive approach for brain tumor prediction and classification using a strong IoT infrastructure with cutting-edge machine learning models and a security approach with the implementation of the AES-ECC hybrid model in the MQTT communication protocol for image data encryption and decryption. We make use of a heterogeneous dataset that we sourced from the Kaggle Dataset platform, which includes four different types of MRI scans of brain tumors from 2870 patients. Our proposed methodology starts with the safe acquisition and transfer of MRI images through an IoT protocol infrastructure to a cloud-based platform. CNN, DenseNet, ResNet and G-Net are some of the sophisticated machine learning models that are used to interpret and analyse these pictures. The computer is trained to identify photos of brain tumors into the appropriate groups using all above four models. According to the data, our suggested CNN model performs better than the others, obtaining an amazing 89% accuracy rate. Nonetheless, we want to achieve even greater improvement in forecast precision by utilising ensemble boosting methodologies. Boosting the CNN model with Ada-Boost, Gradient Boost, XG Boost and Cat Boost algorithms aims to maximize prediction performance. We find that the CNN algorithm combined with XG Boost outperforms all other ensemble methods with an amazing accuracy rate of 97%. This encouraging result highlights how combining cutting-edge machine learning algorithms with IoT infrastructure can lead to better brain tumor classification and prognosis. The creation of more precise and effective diagnostic instruments for the identification of brain tumors is one of our study's many implications, one that will ultimately improve patient outcomes and the healthcare industry.

Image encryption based on combined between linear feedback shift registers and 3D chaotic maps

Protecting information sent through insecure internet channels is a significant challenge facing researchers. In this paper, we present a novel method for image data encryption that combines chaotic maps with linear feedback shift registers in two stages. In the first stage, the image is divided into two parts. Then, the locations of the pixels of each part are redistributed through the random numbers key, which is generated using linear feedback shift registers. The second stage includes segmenting the image into the three primary colors red, green, and blue (RGB); then, the data for each color is encrypted through one of three keys that are generated using three-dimensional chaotic maps. Many statistical tests (entropy, peak signal-noise ratio (PSNR), mean square error (MSE) and correlation) were conducted on a group of images to determine the strength and efficiency of the proposed method, and the result proves that the proposed method provided a good level of safety. The obtained results were compared with those of other methods, and the result of comparing confirms the superiority of the proposed method.

Research on High Reliable Multimode Wireless Communication Technology for UAV

High definition image transmission and remote control are typical applications of UAVs, which has spawned a large number of new scenes. This paper proposes a multimode wireless communication method and image transmission strategy for UAV based on the integration of public network and private network. By building at least two wireless communication links including public network and private network, the image data is encoded after obtaining its channel parameters, and the encoded image data is sent through the two links. The experimental results show that the proposed method improves the reliability and efficiency of data transmission.

IoT-Based Medical Image Monitoring System Using HL7 in a Hospital Database.

In recent years, the healthcare system, along with the technology that surrounds it, has become a sector in much need of development. It has already improved in a wide range of areas thanks to significant and continuous research into the practical implications of biomedical and telemedicine studies. To ensure the continuing technological improvement of hospitals, physicians now also must properly maintain and manage large volumes of patient data. Transferring large amounts of data such as images to IoT servers based on machine-to-machine communication is difficult and time consuming over MQTT and MLLP protocols, and since IoT brokers only handle a limited number of bytes of data, such protocols can only transfer patient information and other text data. It is more difficult to handle the monitoring of ultrasound, MRI, or CT image data via IoT. To address this problem, this study proposes a model in which the system displays images as well as patient data on an IoT dashboard. A Raspberry Pi processes HL7 messages received from medical devices like an ultrasound machine (ULSM) and extracts only the image data for transfer to an FTP server. The Raspberry Pi 3 (RSPI3) forwards the patient information along with a unique encrypted image data link from the FTP server to the IoT server. We have implemented an authentic and NS3-based simulation environment to monitor real-time ultrasound image data on the IoT server and have analyzed the system performance, which has been impressive. This method will enrich the telemedicine facilities both for patients and physicians by assisting with overall monitoring of data.

Design and Implementation of Real-Time Image Acquisition Chip Based on Triple-Hybrid Encryption System

With the improved hardware storage capabilities and the rapid development of artificial intelligence image recognition technology, information is becoming image-oriented. Increasingly sensitive image data needs to be processed. When facing a large amount of real-time sensitive image data encryption and decryption, ensuring both the speed and the security is an urgent demand. This paper proposes an original triple-hybrid encryption system for a real-time sensitive image acquisition chip. This encryption system optimizes the symmetric encryption algorithm AES, asymmetric encryption algorithm ECC, and chip authentication algorithm PUF in pursuit of security, calculation speed, and to ensure that it is lightweight. The three optimized algorithms are further mixed and reused on the circuit level, to ensure mutual protection while making full use of their advantages. Apart from sensitive image protection at the algorithm level, the image chip itself is also protected by an innovative PUF chip authentication method that prevents it from being tampered with and copied. Triple-hybrid encryption system hardware implementation achieves a frequency of 132.5 MHz under the Virtex-5 FPGA with an area of 2834 Slices; with Virtex-7 FPGA, it reaches a frequency of 137.6 MHz with an area of 2716 Slices. The system is also implemented on SMIC 40 nm ASIC, and the clock frequency reaches 480 MHz and the area is 94,812.4 μm2. In terms of computing speed, the peak image encryption speed is 6.15 Gb/s, which meets the real-time image encryption requirement. In terms of hardware resource usage, AES reduced the hardware area by 60.1% compared with the results in other literature, ECC reduced the hardware area by 43.4%, and the PUF hardware area decreased exponentially with the increase in information entropy. The implementation of the three algorithms is reasonable and cost-effective, and the mixture of algorithms does not increase the required capacity of the hardware resource. The triple-hybrid encryption system cooperates with the image acquisition subsystem, storage subsystem, and asynchronous clock subsystem through software control to realize a complete triple-hybrid encryption SoC chip solution, and was successfully taped-out under the SMIC 40 nm process with all constraints passed and a total area of 10.59 mm2.

SoC FPGA-Based Rapid Prototyping of Compressed, Secured and Wireless Image Transmission for Wildlife Surveillance System

Wildlife plays an important role in balancing the earth’s ecosystem. Today, many species of wildlife are threatened with extinction. Images are important input data for wildlife surveillance technology,whichallowsreal situations in the field to be observed and analysed. This project proposed a wireless transmission systemof compressedandsecured imagesusing the SoCFPGA platformfor improving the existing systemin terms of image data collection. Image compression ensuredthat the proposed system wasefficient in terms of data processing, transmission and storage. Image data encryption aimed at ensuring that the security of the transmitted image data would not be hijacked by poachers or non-authorities and ultimately this system wouldtransmit compressed and secured images wirelessly to provide real-time data. The prototype usedLabVIEW 2017 software and NI myRIO (as image transmitter) and a computer (as image receiver) hardware. This platform has been utilisedfor the development of the architectural design of a compression system using the discrete cosine transform (DCT) method, the development of an encryption system using the advanced encryption standards (AES) method and wireless transmission using Wi-Fi. The implementation of DCT on the field-programmable gate array (FPGA) platform allowedthe imagesto be compressed by an average of 44% to shortenthe time used in the transmission process. The AES method guaranteeddata security with images that can only be viewedwhenusing the correct password. Combining both the DCT and AES methods, the rapid prototyping of the wireless transmission of compressed and secured images for a wildlife surveillance system equippedwith a motion sensor and a camera was developed to detect motion, capture imagesand transmit three (3) different image resolutions atdistances of up to 60m.

A Comprehensive Review About Image Encryption Methods

In today’s technology world, data security has a great importance. Because each data type has its own characteristics, there are various methods of providing this security. The main subject of this study is the security of image data which are more complex structures than text data. Using traditional encryption methods alone to ensure security in image data types can create security weaknesses. For this reason, nowadays, some traditional methods are combined with each other or different methods to encrypt image data. In this study, 131 articles were examined and image encryption methods were classified according to the traditional methods they contain. Studies on both colored and gray level images have been handled together. Finally, the images used in the articles were compared with each other in many ways and the results were presented graphically.

AES Image Encryption (Advanced Encryption Standard)

Abstract: An Image Encryption and Decryption Using AES (Advance Encryption Standard) Algorithm is proposed in the project. Due to increasing use of image in various field, it is very important to protect the confidential image data from unauthorized access. The design uses the iterative approach with block size of 128 bit and key size of 128, 192 or 256 bit. The numbers of round for key size of 256 bits is 14 , for 128 bits is 10 and for 192 bits is 12. As secret key increases the security as well as complexity of the cryptography algorithms. In this paper , an algorithm in which the image is an input to AES Encryption to get the encrypted image and then input it to AES Decryption to get the original image is proposed and explained which will further be implemented by me. The paper shows the study in which a system could be used for effective image data encryption and key generation in diversified application areas, where sensitive and confidential data needs to be transmitted along with the image.

Image encryption-then-transmission combining random sub-block scrambling and loop DNA algorithm in an optical chaotic system

In this paper, an image encryption scheme based on random sub-block scrambling and loop deoxyribonucleic acid algorithm in optical chaotic system is proposed. A main laser drives four twin slaver laser pairs to generate high random and complex chaos sequences, which are employed for encryption and transmission. Multiplying eight control parameters (stemming from Hash algorithm between the external key and plain image) by the three groups of optical chaotic sequences, we yield seven pseudo-random sequences. While the fourth optical chaotic carrier is used for transmitting the encrypted image data. Utilizing the random sub-block scrambling and loop deoxyribonucleic acid (DNA) encryption algorithm, we achieve the shuffling and diffusion of image. Furthermore, we carry out a quantitative analysis aimed at the security of image encryption algorithm, and the results show that the image encryption method can offer better security and encryption efficiency. Moreover, we numerically simulate the image data transmission using a chaotic carrier, and decode the information by monitoring the synchronization error between emitter and receiver successfully. The fact implies that the security is further enhanced.

Key Independent Image Deciphering using Neighbourhood Similarity Characteristics and Divide-and-conquer Attack

Aim: The aim of the paper is to analyse the security strength of image encryption schemes which are based on pixel rotation and inversion functions. The key independent image decryption methodologies are presented to obtain original images with intelligible contents from encrypted images using neighbourhood similarity characteristics and divide-and-conquer attack. Background: The efficiency and security strength of secure communication of sensitive data depend on the computing resources and cryptographic strength of encryption schemes. An encryption scheme is cryptographically strong if it does not leave any weakness, vulnerability or pattern which could be exploited by cryptanalyst to obtain the original image from an encrypted image. Prior to the use of any image encryption scheme for multimedia security applications, it should be analysed for its security strength to ensure the safety of information so that an adversary could not extract intelligible information from encrypted image data. A number of encryption schemes developed for image security applications and claimed highly secure but some of these are cryptanalysed successfully and found insecure. Objective: The analysis of image ciphers which encrypt plain images by transforming its pixels using circular rotation or inversion function in a random fashion is carried out for decrypting encrypted images to obtain original images. The encryption schemes, namely ‘Chaotic Image Encryption (CIE)’ and ‘Graphical Image Encryption (GIE)’, were reported secure but we find that these schemes are insecure which can be exploited to obtain meaningful information from the ciphered images. We apply the similarity characteristics of images to mount cryptanalytic attacks on these ciphers and obtain original images without any knowledge of the encryption/decryption keys. These encryption schemes encrypting the specified region-of-interest (ROI) are also analysed to decrypt ROI encrypted images. Method: The methodology of decryption is key independent and based on divide-and-conquer strategy to obtain original images from the given encrypted images. It utilizes the neighbourhood similarity of pixels in an image which is measured in terms of pixel-to-pixel difference between adjacent pixels for pixel inversion based image cipher (GIE) and line-to-line correlation between adjacent lines for pixel rotation based image cipher (CIE). The ROI encrypted and masked encrypted images are also decrypted. Results: Experimental test results show that the decrypted images obtained are quite intelligible and one can understand the contents of decrypted images. It is also seen that an image cipher encrypting the ROI can be decrypted by utilizing unencrypted region surrounding encrypted ROI part of an image. Conclusion: It has been shown that CIE, GIE, ROI and masked encryption schemes reported for image security applications are insecure and not providing adequate security. Such encrypted images can be decrypted successfully without any key knowledge with high intelligibility by considering image similarity characteristics of neighbouring pixels and applying divide-and-conquer attack strategy. Future work: The key independent decryption methodology can be considered to cryptanalyse the encryption schemes under noise attack scenario as future work to see the applicability of decryption methods with respect to increase in noise in encrypted images. Moreover, other modern encryption schemes based on pixel inversion and rotation functions can be analysed for their security strength.

Image Statistics Preserving Encrypt-then-Compress Scheme Dedicated for JPEG Compression Standard.

In this paper, the authors analyze in more details an image encryption scheme, proposed by the authors in their earlier work, which preserves input image statistics and can be used in connection with the JPEG compression standard. The image encryption process takes advantage of fast linear transforms parametrized with private keys and is carried out prior to the compression stage in a way that does not alter those statistical characteristics of the input image that are crucial from the point of view of the subsequent compression. This feature makes the encryption process transparent to the compression stage and enables the JPEG algorithm to maintain its full compression capabilities even though it operates on the encrypted image data. The main advantage of the considered approach is the fact that the JPEG algorithm can be used without any modifications as a part of the encrypt-then-compress image processing framework. The paper includes a detailed mathematical model of the examined scheme allowing for theoretical analysis of the impact of the image encryption step on the effectiveness of the compression process. The combinatorial and statistical analysis of the encryption process is also included and it allows to evaluate its cryptographic strength. In addition, the paper considers several practical use-case scenarios with different characteristics of the compression and encryption stages. The final part of the paper contains the additional results of the experimental studies regarding general effectiveness of the presented scheme. The results show that for a wide range of compression ratios the considered scheme performs comparably to the JPEG algorithm alone, that is, without the encryption stage, in terms of the quality measures of reconstructed images. Moreover, the results of statistical analysis as well as those obtained with generally approved quality measures of image cryptographic systems, prove high strength and efficiency of the scheme’s encryption stage.

Secure image hiding in speech signal by steganography-mining and encryption

<span>Information hiding techniques are constantly evolving due to the increased need for security and confidentiality. This paper proposes a working mechanism in three phases. The first phase includes scrambling the values of the gray image depending on a series of keys that are generated using a quantum chaotic map. The second phase generates hybrid keys by mixing a Zaslavsky and a 3D Hanon map that are used to encrypt the gray image values produced after the scramble. Finally, in the third phase, a new algorithm is suggested to hide the encrypted gray image at random locations within a speech file. This algorithm includes the LSB algorithm to determine the hidden bits and the zero-crossing K-means algorithm in selecting locations mining in a scattered manner so that hackers cannot easily retrieve the hidden data of any hacked person. Also used a fractional fourier transform to choose magnitude value as specific data to hide encoded image data. The measures MSE, PSNR, NSCR, and UACI are using to measure the work efficiency in the encryption algorithm, and in measuring the efficiency of the hidden algorithm, use the measures SNR, PSNR, and MSE. The results of the paper are encouraging and efficient compared to other algorithms that performed the same work. Hence our results show the larger the image dimensions used, the better the values.</span>

Edge-based lightweight selective encryption scheme for digital medical images

Securing digital medical images is increasingly becoming a major concern due to the rapid growth of the amount of medical images transferred over a network and stored on the web servers. However, the enormous size of multimedia and the huge volume of exchanging medical images have motivated the development of low computational complexity methods. This paper presents a lightweight selective encryption scheme to encrypt the edge maps of medical images. The edge map is firstly extracted by an edge detection method. Then, a chaotic map is used to generate a large key space. We propose a one-time pad algorithm to respectively encrypt the significant detected image blocks. The experimental results have proven that the proposed encryption scheme provides an acceptable percentage of encrypted image data. It can also effectively perform image encryption and decryption in a lightweight manner, which makes the scheme a good candidate for real time applications. Moreover, the security analysis demonstrates that our scheme has a robust resistance against various security attacks.

Privacy-Preserving Krawtchouk Moment feature extraction over encrypted image data

Resource-constrained users outsource the massive image data to the cloud to reduce storage and computation overhead locally, but security and privacy concerns seriously hinder the applications of outsourced image processing services. Besides, existing image processing solutions in the encrypted domain still bring high computation overhead, and even lead to characteristic loss. To this end, we propose a Privacy-Preserving Krawtchouk Moment (PPKM) feature extraction framework over encrypted image data by utilizing the Paillier cryptosystem. First, a mathematical framework for PPKM implementation and image reconstruction is presented in the encrypted domain. Then, the detailed expanding factor and upper bound analysis shows that plaintext Krawtchouk moment and plaintext image reconstruction can be realized over encrypted image with PPKM. Furthermore, the computation complexity of PPKM can be significantly reduced with the block-based parallel algorithm. Experimental results verify that the PPKM is feasible and acceptable in practice in terms of image reconstruction capability and image recognition accuracy.

An Improved Discrete Patch Based Reversible Data Hiding For Encoded Color Images

This paper proposes a system for encrypting images which is performed by patch wise separable reversible data. In the beginning, with the help of encryption key, a content writer prepares the unique uncompressed image. Then, the data-hider abridge encrypted images with least significant using data smacking key therefore to construct a sparse path that can incorporate with some additional data. The encrypted image data consisting of additional data, will aid the receiver to use only one encryption key to recall both additional data and image after decryption. The proposed system enables the receiver, to bring out the data and retrieving the actual content without an error by using both data-hiding key and encryption keys. The key generated is stored and the log is maintained. Data transmission through public communication system is unsecure due to be inaccuracy and improper exploitation by eavesdropper. The specific problem can be resolved by the technique Steganography, where the hidden messages are written in a way where it is only understood by the sender and intend recipient which gives the complete security for the messages. This proposed method includes Advanced Encryption Standard algorithm for encrypting both the image and the data. In order to achieve efficient working of encryption process, Separable Patch wise Reversible Data Hiding (SPRDH) algorithm is used in rescindable manner. The performance are analyzed using available Classical database images with the metrics Bits per Pixel (BPP). Peak Signal Noise Ratio (PSNR) and Mean Square Error (MSE).

DNA and Plaintext Dependent Chaotic Visual Selective Image Encryption

Visual selective image encryption can both improve the efficiency of the image encryption algorithm and reduce the frequency and severity of attacks against data. In this article, a new form of encryption is proposed based on keys derived from Deoxyribonucleic Acid (DNA) and plaintext image. The proposed scheme results in chaotic visual selective encryption of image data. In order to make and ensure that this new scheme is robust and secure against various kinds of attacks, the initial conditions of the chaotic maps utilized are generated from a random DNA sequence as well as plaintext image via an SHA-512 hash function. To increase the key space, three different single dimension chaotic maps are used. In the proposed scheme, these maps introduce diffusion in a plain image by selecting a block that have greater correlation and then it is bitwise XORed with the random matrix. The other two chaotic maps break the correlation among adjacent pixels via confusion (row and column shuffling). Once the ciphertext image has been divided into the respective units of Most Significant Bits (MSBs) and Least Significant Bit (LSBs), the host image is passed through lifting wavelet transformation, which replaces the low-frequency blocks of the host image (i.e., HL and HH) with the aforementioned MSBs and LSBs of ciphertext. This produces a final visual selective encrypted image and all security measures proves the robustness of the proposed scheme.