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The need for cybersecurity increases to protect the exchange of information for improving the data privacy. This paper presents an investigation of the encryption efficiency of the chaotic-based image block ciphering in the spatial and Fractional Fourier Transform (FrFT) domains. The main aim of this investigation is to examine the efficiency of different chaotic maps, while considering the parameters of the FrFT as additional keys for encryption and achieving reliable cybersecurity for robust image communication. In this paper, Cat, Baker, and Logistic map confusion approaches are applied in the spatial and FrFT domains to study and analyze the cybersecurity and ciphering efficiency of chaos-based image cryptosystems. The confusion features of the chaotic maps in spatial and FrFT domains are investigated using information entropy, differential analysis, histograms, visual observation, attack analysis, impact of noise, and encryption quality tests. Simulation results prove that the chaotic-based image encryption in the FrFT domain increases the efficiency of the confusion process and achieves a high nonlinear relation between the plainimage and the cipherimage in a symmetric ciphering approach. Moreover, the results demonstrate that the Cat-FrFT scheme is more susceptible to channel noise attacks than the Baker-FrFT and the Logistic-FrFT schemes. Hence, they can be implemented efficiently in the scenarios of noisy channels due to their high robustness to channel noise.

This paper investigates and presents a block-based opto-color cipher using double random phase encoding (DRPE) with different block sizes. The color plainimage is divided into equal-sized blocks and then converted to an optical signal by an optical emitter. The obtained optical signal is encrypted by employing the DRPE technique, which applies two types of phase modulation, time, and Fourier domains. Finally, the optical color cipherimage is, upon detection, converted to digital format by a charge-coupled device digital camera. Experiments and security analysis show that the proposed block-based optical color image cipher using DRPE with increased block size is secure, effective, and including a good immunity to channel noise. INDEX TERMS DRPE, Fourier domain, optical color image, time domain, and image encryption.

In this paper, we describe a new cryptographic primitive called (One-Way) Signature Chaining. Signature chaining is essentially a method of generating a chain of signatures on the same message by different users. Each signature acts as a "link" of the chain. The one-way-ness implies that the chaining process is one-way in the sense that more links can be easily added to the chain. However, it is computationally infeasible to remove any intermediate links without removing all the links. The signatures so created are called chain signatures (CS). We give precise definitions of chain signatures and discuss some applications in trust transfer. We then present a practical construction of a CS scheme that is secure (in the random oracle model) under the Computational Diffie-Hellman (CDH) assumption in bilinear maps.

Rapid scaling of using the Internet of Things (IoT) technology has been seen recently in numerous applications in healthcare to deliver proper services. This was motivated by the declining size and cost of the employed IoT devices. Developing such technology has been well investigated in the literature; however, few studies have explored the factors influencing its adaptation in the healthcare setting. In this study, we investigate the core factors that influence the acceptance of using IoT for Healthcare Purposes in the Kingdom of Saudi Arabia (KSA). Accordingly, a theoretical framework, based on the Technology Acceptance Model (TAM), was developed and tested empirically. The modified model added variables that provide a better explanation of the acceptance of healthcare technology. To ground our conceptual idea, a survey was designed and performed on 407 patients (207 males, 200 females). The Partial Least Square Structural Equation Modeling (SEM) technique was applied to analyze the effect of eight hypothesized predicting constructs on the collected data. Results revealed that cost, privacy concerns, and perceived usefulness were the most significant predictors of behavioral intention to use. However, attitude and perceived connectedness were found to be irrelevant in predicting the intention to use IoT. Ultimately, results found that there is no correlation between gender and behavioral intention.

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