Unmanned aerial vehicles face GPS spoofing and jamming that can compromise navigation and safety. We present an anomaly detection method that achieves both high accuracy and interpretability, enabling UAV operators to understand why an alert is triggered, which enables timely responses and builds trust in autonomous detection systems operating in safety-critical environments. We use five classifiers, including XGBoost, Support Vector Machine, K-Nearest Neighbor, Random Forest, and Naive Bayes, trained on a UAV dataset containing 3622 samples for spoofing detection and 6445 for jamming detection made in PX4 and Gazebo with benign flight and attack cases. After feature scaling and reduction, X... More >

The rapid pace of technological developments in the digital age has transformed the tourism sector, spawning virtual tourism, an emerging platform through which tourists are able to visit their destination using augmented reality (AR) and virtual reality (VR) for interactive experiences. Such technological transformation creates significant cybersecurity challenges, such as data breaches, violations of users’ privacy, and vulnerabilities on platforms. Therefore, our work uses bibliometric approaches to examine the growing body of research on virtual tourism cybersecurity. A total of 1145 publications were retrieved using the specified query, which includes studies on the dangers of data th... More >

The Internet of Things (IoT) is a technological ecosystem that interconnects physical devices via the Internet to enable data exchange and coordinated operations, among which the Internet of Drones (IoD) represents a specialized application integrating drone technology with IoT for remote control and data transmission. With the adoption of fifth-generation (5G) mobile communication networks in IoD environments, drones can transmit high-quality data and respond to user requests with reduced latency. In recent years, various authentication schemes using temporary credentials have been proposed to allow users and drones to establish session keys with the assistance of a control server; however,... More >

Intrusion Detection Systems (IDS) play a critical role in protecting modern networks, but traditional centralized designs raise serious concerns regarding data privacy, trust, and scalability. Federated Learning (FL) reduces privacy risks through decentralized model training, and blockchain enhances trust by providing immutability and transparency. Combining these technologies creates a promising paradigm for secure and trustworthy IDS. This paper presents a comprehensive survey of blockchain-federated IDS with a particular focus on privacy and trust. The key contribution is a multi-dimensional taxonomy that integrates IDS architectures, FL strategies, blockchain types, and consensus mechani... More >

Presents the introductory editorial for the inaugural issue of this title. More >