IoT-Based Multi-Dimensional Chaos Mapping System for Secure and Fast Transmission of Visual Data in Smart Cities

A “smart city” sends data from many sensors to a cloud server for local authorities and the public to connect. Smart city residents communicate mostly through images and videos. Many image security algorithms have been proposed to improve locals’ lives, but a high-class redundancy method with a small space requirement is still needed to acquire and protect this sensitive data. This paper proposes an IoT-based multi-dimensional chaos mapping system for secure and fast transmission of visual data in smart cities, which uses the five dimensional Gauss Sine Logistic system to generate hyper-chaotic sequences to encrypt images. The proposed method also uses pixel position permutation and Singular Value Decomposition with Discrete fractional cosine transform to compress and protect the sensitive image data. To increase security, we use a chaotic system to construct the chaotic sequences and a diffusion matrix. Furthermore, numerical simulation results and theoretical evaluations validate the suggested scheme’s security and efficacy after compression encryption.publishedVersio

Enhanced image encryption scheme with new mapreduce approach for big size images

Achieving a secured image encryption (IES) scheme for sensitive and confidential data communications, especially in a Hadoop environment is challenging. An accurate and secure cryptosystem for colour images requires the generation of intricate secret keys that protect the images from diverse attacks. To attain such a goal, this work proposed an improved shuffled confusion-diffusion based colour IES using a hyper-chaotic plain image. First, five different sequences of random numbers were generated. Then, two of the sequences were used to shuffle the image pixels and bits, while the remaining three were used to XOR the values of the image pixels. Performance of the developed IES was evaluated in terms of various measures such as key space size, correlation coefficient, entropy, mean squared error (MSE), peak signal to noise ratio (PSNR) and differential analysis. Values of correlation coefficient (0.000732), entropy (7.9997), PSNR (7.61), and MSE (11258) were determined to be better (against various attacks) compared to current existing techniques. The IES developed in this study was found to have outperformed other comparable cryptosystems. It is thus asserted that the developed IES can be advantageous for encrypting big data sets on parallel machines. Additionally, the developed IES was also implemented on a Hadoop environment using MapReduce to evaluate its performance against known attacks. In this process, the given image was first divided and characterized in a key-value format. Next, the Map function was invoked for every key-value pair by implementing a mapper. The Map function was used to process data splits, represented in the form of key-value pairs in parallel modes without any communication between other map processes. The Map function processed a series of key/value pairs and subsequently generated zero or more key/value pairs. Furthermore, the Map function also divided the input image into partitions before generating the secret key and XOR matrix. The secret key and XOR matrix were exploited to encrypt the image. The Reduce function merged the resultant images from the Map tasks in producing the final image. Furthermore, the value of PSNR did not exceed 7.61 when the developed IES was evaluated against known attacks for both the standard dataset and big data size images. As can be seen, the correlation coefficient value of the developed IES did not exceed 0.000732. As the handling of big data size images is different from that of standard data size images, findings of this study suggest that the developed IES could be most beneficial for big data and big size images

A novel symmetric image cryptosystem resistant to noise perturbation based on S8 elliptic curve S-boxes and chaotic maps

The recent decade has seen a tremendous escalation of multimedia and its applications. These modern applications demand diverse security requirements and innovative security platforms. In this manuscript, we proposed an algorithm for image encryption applications. The core structure of this algorithm relies on confusion and diffusion operations. The confusion is mainly done through the application of the elliptic curve and S8 symmetric group. The proposed work incorporates three distinct chaotic maps. A detailed investigation is presented to analyze the behavior of chaos for secure communication. The chaotic sequences are then accordingly applied to the proposed algorithm. The modular approach followed in the design framework and integration of chaotic maps into the system makes the algorithm viable for a variety of image encryption applications. The resiliency of the algorithm can further be enhanced by increasing the number of rounds and S-boxes deployed. The statistical findings and simulation results imply that the algorithm is resistant to various attacks. Moreover, the algorithm satisfies all major performance and quality metrics. The encryption scheme can also resist channel noise as well as noise-induced by a malicious user. The decryption is successfully done for noisy data with minor distortions. The overall results determine that the proposed algorithm contains good cryptographic properties and low computational complexity makes it viable to low profile applications

Entropy in Image Analysis III

Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future

Image encryption under spatial domain based on modify 2D LSCM chaotic map via dynamic substitution-permutation network

Image encryption has become an important application aspect of information security. Most attempts are focused on increasing the security aspect, the quality of the resulting image, and the time consumed. On the other hand, dealing with the color image under the spatial domain in this filed is considered as another challenge added to the proposed method that make it sensitivity and difficulty. The proposed method aims to encode a color image by dealing with the main color components of the red (R), green (G), and blue (B) components of a color image to strengthen the dependence of each component by modifying a two dimensional logistic- sine coupling map (2D- LSCM). This is to satisfy the statistical features and reduce time-consumption, and benefit from a mixing step of the second of advanced encryption standard (AES) candidates (serpent block cipher) and modified it to achieve in addition of confusion and diffusion processes. The experimental results showed that our proposed method had the ability to resist against statistical attacks and differential attacks. It also had a uniform histogram, a large key space, complex and faster, closer Shannon entropy to 8, and low correlation values between two adjacent pixels compared with other methods

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas

Multistable dynamics and control of a new 4D memristive chaotic Sprott B system

This work proposes and investigates the dynamic behavior of a new memristive chaotic Sprott B system. One of the interesting features of this system is that it has a bias term that can adjust the symmetry of the proposed model, inducing both homogeneous and heterogeneous behaviors. Indeed, the introduced memristive system can turn from rotational symmetry (RS) to rotational symmetry broken (RSB) system in the presence or the absence of this bias term. In the RS system (i.e., absence of the bias term), pairs of symmetric attractors are formed, and the scenario of attractor merging is observed. Coexisting symmetric attractors and bifurcations with up to four solutions are perfectly investigated. In the RSB system (i.e., the bias term is non-zero), many interesting phenomena are demonstrated, including asymmetric attractors, coexisting asymmetric bifurcations, various types of coexisting asymmetric solutions, and period-doubling transition to chaos. We perfectly demonstrate that the new asymmetric/symmetric memristive system exhibits the exciting phenomenon of partial amplitude control (PAC) and offset boosting. Also, we show how it is possible to control the amplitude and the offset of the chaotic signals generated for some technological exploitation. Finally, coexisting solutions (i.e., multistability) found in the novel memristive system are further controlled based on a linear augmentation (LA) scheme. Our numerical findings demonstrated the effectiveness of the control technic through interior crisis, reverse period-doubling scenario, and symmetry restoring crisis. The coupled memristive system remains stable with its unique survived periodic attractor for higher values of the coupling strength

A Chaotic Quadratic Oscillator with Only Squared Terms: Multistability, Impulsive Control, and Circuit Design

Here, a chaotic quadratic oscillator with only squared terms is proposed, which shows various dynamics. The oscillator has eight equilibrium points, and none of them is stable. Various bifurcation diagrams of the oscillator are investigated, and its Lyapunov exponents (LEs) are discussed. The multistability of the oscillator is discussed by plotting bifurcation diagrams with various initiation methods. The basin of attraction of the oscillator is discussed in two planes. Impulsive control is applied to the oscillator to control its chaotic dynamics. Additionally, the circuit is implemented to reveal its feasibility