Chaos-based cryptosystems have been an active area of research in recent years. Although these algorithms are not standardized like AES, DES, RSA, etc., chaos-based cryptosystems like Chebyshev polynomials can provide additional security when used with standard public key cryptosystems like RSA and El-gamal. Standard encryption algorithms such as AES have always been the primary choice, but when it comes to image or video encryption, many researchers recommend chaos-based encryption techniques due to their computational efficiency. This paper presents a survey on the most up-to-date chaos-based image encryption techniques and classifies them into spatial, temporal and spatiotemporal domains for better understanding. The significant improvements in the field of image encryption are discussed. In addition, comparative analysis is performed to validate the evaluation matrices for quantifying the encryption algorithms’ security and performance in recent papers.

Internet of Things (IoT) technology is increasingly pervasive in all aspects of our life and its usage is anticipated to significantly increase in future Smart Cities to support their myriad of revolutionary applications. This paper introduces a new architecture that can support several IoT-enabled smart home use cases, with a specified level of security and privacy preservation. The security threats that may target such an architecture are highlighted along with the cryptographic algorithms that can prevent them. An experimental study is performed to provide more insights about the suitability of several lightweight cryptographic algorithms for use in securing the constrained IoT devices used in the proposed architecture. The obtained results showed that many modern lightweight symmetric cryptography algorithms, as CLEFIA and TRIVIUM, are optimized for hardware implementations and can consume up to 10 times more energy than the legacy techniques when they are implemented in software. Moreover, the experiments results highlight that CLEFIA significantly outperforms TRIVIUM under all of the investigated test cases, and the latter performs 100 times worse than the legacy cryptographic algorithms tested.

Pseudo-random number generators (PRNGs) are one of the building blocks of cryptographic methods and therefore, new and improved PRNGs are continuously developed. In this study, a novel method to generate pseudo-random sequences using coupled map lattices is presented. Chaotic maps only show their chaotic behaviour for a specified range of control parameters, what can restrict their application in cryptography. In this work, generalised symmetric maps with adaptive control parameter are presented. This novel idea allows the user to choose any symmetric chaotic map, while ensuring that the output is a stream of independent and random sequences. Furthermore, to increase the complexity of the generated sequences, a lattice-based structure where every local map is linked to its neighbouring node via coupling factor has been used. The dynamic behaviour and randomness of the proposed system has been studied using Kolmogorov–Sinai entropy, bifurcation diagrams and the NIST statistical suite for randomness. Experimental results show that the proposed PRNG provides a large key space, generates pseudo-random sequences and is computationally suitable for IoT devices.

Background: With an increasing number of digital health apps available in app stores, it is important to assess these technologies reliably regarding their quality. This is done to mitigate the risks associated with their use. There are many different guidelines, methods, and metrics available to assess digital health apps with regard to their quality. Objective: This study aimed to give a holistic summary of the current methods and “condition agnostic” frameworks that are broadly applicable for the quality assessment of all digital health apps. Methods: A systematic search of literature was conducted on 4 databases: Scopus, PubMed, ACM Digital Library, and IEEE Xplore. We followed the PICOS (Population, Patient, or Problem; Intervention; Comparison; Outcomes; and Study Design) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodologies when conducting this umbrella review. The search was conducted on January 26, 2024, for review articles published between 2018 and 2023. We identified 4781 candidate papers for inclusion; after title and abstract screening, 39 remained. After full-text analysis, we included 15 review articles in the full review. Results: Of the 15 review articles, scoping reviews were the most common (n=6, 40%), followed by systematic reviews (n=4, 27%), narrative reviews (n=4, 27%), and a rapid review (n=1, 7%). A total of 4 (27%) review articles proposed assessment criteria for digital health apps. “Data privacy and/or security” was the most mentioned criterion (n=13, 87%) and “Cost” was the least mentioned criterion (n=1, 7%) for the assessment of digital health apps. The Mobile App Rating Scale was the most frequently used framework for quality assessment of digital health apps. Conclusions: There is a lack of unity or consolidation across identified frameworks, as most do not meet all the identified criteria from the reviewed articles. Safety concerns associated with the use of digital health apps may be mitigated with the use of quality frameworks.

Image and video data make up a significant portion of the content shared over the Internet and social media. The use of image and video communication allows more information to be shared while simultaneously presenting higher risks in terms of data security. The traditional encryption schemes are general purpose; however, to encrypt image and video data, application-specific encryption solutions are needed. An image or a video frame comprises a two-dimensional matrix where pixel intensity values are integers in range [0,255], leading to data redundancy problems. Moreover, the bulk amount of image and video data adds another challenge when deploying security primitives. In this paper, a novel coupled map lattice system-based image cryptosystem has been proposed that uses generalised symmetric maps for generation of pseudo-random sequences. The generalization of symmetric maps allows the user to choose the source of pseudo-random sequence generation by varying a single control parameter. Other adaptive control parameters ensure an adequate degree of randomness in the generated sequences. The proposed encryption system relies on three independent sources of pseudo-random sequence generators, which are further re-randomized before the final encryption process. Comprehensive experimentation has been performed to test the proposed system against various attack models on publicly available datasets. A detailed comparative analysis has also been conducted with existing state-of-the-art image encryption techniques. Results show that the proposed algorithm provides high information entropy, negative correlation, large key space, and high sensitivity to key variations, and is resistant to various types of attacks, including chosen-text, statistical, and differential attacks.

Optimal Foraging Theory (OFT) integrates both the consumer and the resource, yet their simultaneous assessment is uncommon. Vultures represent an ideal model for OFT studies because carrion requires no capture effort and minimal handling, allowing them to focus primarily on food searching. Here, we combined GPS tracking of 61 Iberian griffon vultures (consumers) with photo-trapping monitoring of 49 carcasses (resources) to assess the determinants of vulture foraging and the consequences for carrion consumption in two areas with different carrion abundances. First, we determined the importance of different factors (distance to the resource, hunger and competition) in the decisions of individuals of whether to descend or not on a carcass. Second, we compared carrion consumption patterns (time of carcass discovery and consumption, and maximum number of vultures gathered around the carcass) between areas. We found that distance, rather than hunger, is the primary factor determining whether a vulture descends to a carcass. In parallel, carrion was consumed similarly in areas with different resource availabilities. These findings indicate that vultures tend to eat whenever a nearby opportunity arises, consistent with a type-I functional response.