Physical layer authenticated image encryption for Iot network based on biometric chaotic signature for MPFrFT OFDM system

In this paper, a new physical layer authenticated encryption (PLAE) scheme based on the multi-parameter fractional Fourier transform–Orthogonal frequency division multiplexing (MP-FrFT-OFDM) is suggested for secure image transmission over the IoT network. In addition, a new robust multi-cascaded chaotic modular fractional sine map (MCC-MF sine map) is designed and analyzed. Also, a new dynamic chaotic biometric signature (DCBS) generator based on combining the biometric signature and the proposed MCC-MF sine map random chaotic sequence output is also designed. The final output of the proposed DCBS generator is used as a dynamic secret key for the MPFrFT OFDM system in which the encryption process is applied in the frequency domain. The proposed DCBS secret key generator generates a very large key space of (Formula presented.). The proposed DCBS secret keys generator can achieve the confidentiality and authentication properties. Statistical analysis, differential analysis and a key sensitivity test are performed to estimate the security strengths of the proposed DCBS-MP-FrFT-OFDM cryptosystem over the IoT network. The experimental results show that the proposed DCBS-MP-FrFT-OFDM cryptosystem is robust against common signal processing attacks and provides a high security level for image encryption application. © 2023 by the authors

Medical image encryption techniques: a technical survey and potential challenges

Among the most sensitive and important data in telemedicine systems are medical images. It is necessary to use a robust encryption method that is resistant to cryptographic assaults while transferring medical images over the internet. Confidentiality is the most crucial of the three security goals for protecting information systems, along with availability, integrity, and compliance. Encryption and watermarking of medical images address problems with confidentiality and integrity in telemedicine applications. The need to prioritize security issues in telemedicine applications makes the choice of a trustworthy and efficient strategy or framework all the more crucial. The paper examines various security issues and cutting-edge methods to secure medical images for use with telemedicine systems

Efficient and secure image encryption using key substitution process with discrete wavelet transform

Over the past few years, there has been a rise in the utilization of chaotic encryption algorithms for securing images. The majority of chaos-based encryption algorithms adhere to the conventional model of confusion and diffusion, which typically involves either implementing multiple encryption rounds or employing a single round of intricate encryption to guarantee robust security. However, such kind of approaches reduces the computational efficiency of the encryption process but compromises security. There is a trade-off between security and computational efficiency. Prioritizing security may require high computational processes. To overcome this issue, a key substitution encryption process with discrete wavelet transform (KSP-DWT) is developed in the proposed image encryption technique (IET). Based on KSP-DWT and IET, the abbreviation of the proposed work is used in this paper as KSP-DWT-IET. The proposed KSP-DWT algorithm employs a key scheming technique to update the initial keys and uses a novel substitution method to encrypt digital images of different sizes. Additionally, the integration of DWT can result in the compression of frequency sub-bands of the source image, leading to lower computational overheads without compromising the security of the encryption. The KSP-DWT-IET performs a single encryption round and is highly secure and efficient. The simulation results and security analysis conducted on KSP-DWT-IET confirm its effectiveness in ensuring high-security image encryption while minimizing computational overhead. The proposed encryption technique undergoes various security analyses, including entropy, contrast, correlation, energy, NPCR (Number of Pixel Changes Rate), UACI (Unified Average Change Intensity) and computational complexity. The statistical values obtained for such parameters are 7.9991, 10.9889, 0.0001, 0.0152, 33.6767, and 33.6899, respectively, which indicate that the encryption technique performs very well in terms of security and computational efficiency. The proposed encryption scheme is also analyzed for its computational time in addition to its security. The analysis shows that the scheme can efficiently encrypt images of varying sizes with a high level of security in a short amount of time (i.e., 2 ms). Therefore, it is feasible to use this encryption scheme in real-time applications without causing any significant delays. Moreover, the key space of the proposed encryption scheme is large enough (i.e. Keyspace ) to resist the brute force attack

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

Cybersecurity and the Digital Health: An Investigation on the State of the Art and the Position of the Actors

Cybercrime is increasingly exposing the health domain to growing risk. The push towards a strong connection of citizens to health services, through digitalization, has undisputed advantages. Digital health allows remote care, the use of medical devices with a high mechatronic and IT content with strong automation, and a large interconnection of hospital networks with an increasingly effective exchange of data. However, all this requires a great cybersecurity commitment—a commitment that must start with scholars in research and then reach the stakeholders. New devices and technological solutions are increasingly breaking into healthcare, and are able to change the processes of interaction in the health domain. This requires cybersecurity to become a vital part of patient safety through changes in human behaviour, technology, and processes, as part of a complete solution. All professionals involved in cybersecurity in the health domain were invited to contribute with their experiences. This book contains contributions from various experts and different fields. Aspects of cybersecurity in healthcare relating to technological advance and emerging risks were addressed. The new boundaries of this field and the impact of COVID-19 on some sectors, such as mhealth, have also been addressed. We dedicate the book to all those with different roles involved in cybersecurity in the health domain

Sensor Signal and Information Processing II

In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing