Vehicular Ad hoc NETworks (VANETs) are a key part of the Intelligent Transport Systems (ITS) as they constitute an intelligent transport network where vehicles and some infrastructure collaborate to exchange messages about traffic, accidents, etc. In such context, security becomes a key component to ensure that exchanged messages were not modified or inserted for example. Consequently, a wide variety of research contributions have been recently presented to cope with this issue. This paper presents a review of most recent papers dealing with security issues in VANETs. Hence, it presents an overview of VANETs and mainly their characteristics as well as their main applications. Then, the main security challenges faced by VANETs are introduced. This is done by first listing their main security requirements, second by establishing attackers' profiles, and their attacks and third by introducing some security solutions. Finally, the opportunities and challenges related to VANETs security are presented such as Trust, Internet of Vehicle, etc.This article is categorized under: Digital and Multimedia Science > Vehicle Forensics Digital and Multimedia Science > Mobile Forensics Digital and Multimedia Science > IoT Forensics

A Vehicular Ad hoc NETwork (VANET) is a self-organized network formed by connected vehicles, which allows the exchange of useful traffic information in a timely manner. In such a context, evaluating the reliability of transmissions is vital. Trust can be used to promote such healthy collaboration. In fact, trust enables collaborating vehicles to counter uncertainty and suspicion by establishing trustworthy relationships. The main contribution of this paper is the proposition of a trust-based security scheme for message exchange in a VANET called TSME. Because of VANET characteristics, including dynamicity and high speed, we first proposed a VANET Grouping Algorithm (VGA); a suitable clustering algorithm organizing the network into groups with elected Group-Heads. Second, built on the VGA, we defined our trust management scheme dealing with vehicles’ reputations. Finally, we proposed a formal specification of the scheme using an inference system, and conducted a formal validation to assess its completeness and soundness rather than conducting simulations where some potentially rare conflicting or malfunctioning situations might not be detected. Soundness was proven by showing that there were no conflicts in our scheme, and completeness was established by assessing that all potential situations could be handled. The results obtained showed that our scheme for evaluating the veracity of exchanged messages is formally sound and complete.

Trust allows collaborating entities to cope with their uncertainty especially when these collaborations are the bedrock of the network existence such as in Mobile Ad hoc NETworks (MANET). The trustworthiness of collaborators can be evaluated using reputations. Reputation is an appreciation of the node credibility created through past actions. It can be calculated using direct observations and/or using other nodes appreciations exchanged through recommendations. Unfortunately, some nodes may be attempted to disturb the network by sending faked recommendations in order to decrease the reputation of a benevolent node or to increase the one of an attacker. That’s collusion attack. The main contribution of this paper concerns then, the proposition of collusion prevention and detection process in a trust based MANET.

Deaf and hearing-impaired individuals rely on sign language, a visual communication system using hand shapes, facial expressions, and body gestures. Sign languages vary by region. For example, Arabic Sign Language (ArSL) is notably different from American Sign Language (ASL). This project focuses on creating an Arabic Sign Language Recognition (ArSLR) System tailored for healthcare, aiming to bridge communication gaps resulting from a lack of sign-proficient professionals and limited region-specific technological solutions. Our research addresses limitations in sign language recognition systems by introducing a novel framework centered on ResNet50ViT, a hybrid architecture that synergistically combines ResNet50’s robust local feature extraction with the global contextual modeling of Vision Transformers (ViT). We also explored a tailored Vision Transformer variant (SignViT) for Arabic Sign Language as a comparative model. Our main contribution is the ResNet50ViT model, which significantly outperforms existing approaches, specifically targeting the challenges of capturing sequential hand movements, which traditional CNN-based methods struggle with. We utilized an extensive dataset incorporating both static (36 signs) and dynamic (92 signs) medical signs. Through targeted preprocessing techniques and optimization strategies, we achieved significant performance improvements over conventional approaches. In our experiments, the proposed ResNet50-ViT achieved a remarkable 99.86% accuracy on the ArSL dataset, setting a new state-of-the-art, demonstrating the effectiveness of integrating ResNet50’s hierarchical local feature extraction with Vision Transformer’s global contextual modeling. For comparison, a fine-tuned Vision Transformer (SignViT) attained 98.03% accuracy, confirming the strength of transformer-based approaches but underscoring the clear performance gain enabled by our hybrid architecture. We expect that RAFID will help deaf patients communicate better with healthcare providers without needing human interpreters.

As governments and organizations seek to strengthen cybersecurity measures, ethical considerations play a crucial role in shaping effective and responsible policies. This research article explores the ethical dimensions of cybersecurity policymaking, focusing on the balance between security imperatives and individual privacy rights. Drawing on principles of ethics, human rights, and legal frameworks, the article discusses challenges and dilemmas faced by policymakers in ensuring cybersecurity without compromising privacy and civil liberties. It proposes a set of ethical guidelines and best practices for designing and implementing cybersecurity policies that are both effective and respectful of fundamental rights and values.