Search Results (186)

Wi-Fi networks used in smart grids are essential for enabling communication between smart meters and data aggregation units. A key challenge, however, is the ability to hide the existence and traffic patterns of these communications, so that sensitive information exchanges cannot be easily detected or intercepted. Unfortunately, most existing solutions do not provide support for traffic prioritization and steganographic channel encryption. In this paper, we propose a novel covert channel with Quality of Service (QoS) and encryption support for smart grid environments based on the IEEE 802.11 standard. We introduce an original steganographic approach that leverages the backoff mechanism, the Enhanced Distributed Channel Access (EDCA) function, frame aggregation, and the StegoPaddingCipher algorithm. This design ensures QoS-aware traffic handling while enhancing security through encryption of the transmitted covert data. The proposed protocol was implemented and evaluated using the ns-3 simulator, where it achieved excellent performance results. The system maintained high efficiency even under heavily saturated network conditions with additional background traffic generated by other nodes. The proposed covert channel offers an innovative and secure method for transmitting substantial volumes of QoS-related data within smart grid environments. Full article

In the contemporary digital landscape, AI (Artificial Intelligence) emerged as a pivotal tool in enhancing the defense technologies developed across the entire network infrastructure. As reliance on AI-based decision-making grew, so did the imperative need for interpretability, transparency, and trustworthiness, leading to the development and integration of XAI (eXplainable Artificial Intelligence). This research paper provides a comprehensive overview of the current state of the art in XAI approaches that can be effectively implemented for network traffic monitoring, especially in critical digital infrastructures. The main contribution of this research article consists of the comparative analysis of the XAI SHAP (Shapley Additive Explanation) method applied to different datasets obtained from real-time network traffic monitoring, utilizing several representative parameters, which demonstrates the performance, vulnerabilities, and limitations of the proposed method, and also the security implications of the system resources from a cybersecurity perspective. Experimental results show that Ethernet networks offer higher predictability and clearer decision boundaries. Consequently, they are a safer solution for deployment in sensitive network architectures. In contrast, BYOD (Bring Your Own Device) Wi-Fi environments exhibit greater randomness. Full article

Honey bees are very important to the ecological environment and human society, contributing significantly to biodiversity and global food security, with an estimated annual impact of $15 billion in crop pollination in the USA. Over 62% of honey bee colony decline has been observed between June 2024 and February 2025. This study investigates bee stress level monitoring due to external disturbances like mechanical vibrations by measuring internal air temperature, relative humidity, and CO₂ gas concentration levels of beehives. A new wireless sensor board for real-time monitoring of honey bee colonies was designed, built, and validated. The board incorporates NDIR-based SCD30 and SCD41 sensors for CO₂, temperature, and humidity monitoring, integrated with a custom-designed two-layer printed circuit board and a Particle Argon^TM microprocessor for Wi-Fi communication. The developed board was tested and validated with live beehives in summer and winter of 2024 and 2025. The experimental study results showed the adequacy of the built sensor board. Bee colony responses on the applied stimuli (knocks) show that bees responded with a temperature increase of over 5 °C, CO₂ concentration increase by 3000 to over 10,000 ppm, and, at the same time, relative humidity drop by about 10% inside beehives. Full article

The recent advancements in technologies such as artificial intelligence (AI), computer vision (CV), and Internet of Things (IoT) have significantly extended various fields, particularly in surveillance systems. These innovations enable real-time facial recognition processing, enhancing security and ensuring safety. However, mobile robots are commonly employed in surveillance systems to handle risky tasks that are beyond human capability. In this paper, we present a prototype of a cost-effective mobile surveillance robot built on the Raspberry PI 4, designed for integration into various industrial environments. This smart robot detects intruders using IoT and face recognition technology. The proposed system is equipped with a passive infrared (PIR) sensor and a camera for capturing live-streaming video and photos, which are sent to the control room through IoT technology. Additionally, the system uses face recognition algorithms to differentiate between company staff and potential intruders. The face recognition method combines high-order statistical features and evidence theory to improve facial recognition accuracy and robustness. High-order statistical features are used to capture complex patterns in facial images, enhancing discrimination between individuals. Evidence theory is employed to integrate multiple information sources, allowing for better decision-making under uncertainty. This approach effectively addresses challenges such as variations in lighting, facial expressions, and occlusions, resulting in a more reliable and accurate face recognition system. When the system detects an unfamiliar individual, it sends out alert notifications and emails to the control room with the captured picture using IoT. A web interface has also been set up to control the robot from a distance through Wi-Fi connection. The proposed face recognition method is evaluated, and a comparative analysis with existing techniques is conducted. Experimental results with 400 test images of 40 individuals demonstrate the effectiveness of combining various attribute images in improving human face recognition performance. Experimental results indicate that the algorithm can identify human faces with an accuracy of 98.63%. Full article

Volunteer tourism is garnering growing attention across various fields, allowing tourists to both consume and co-produce tourism services. In agriculture, however, this remains underexplored, despite a worsening farm labour shortage due to ageing populations and a lack of successors, particularly in industrialised nations. This issue threatens farm productivity and food security. This paper addresses this research gap by examining paid volunteer tourism platforms in Japan. It presents a framework highlighting the co-creation of local tourism demand and analyses wage determinants across 138 farms. Results show that corporate farms engaged in direct sales offer higher wages, especially when prices are elevated or locations are remote, suggesting wage premiums reflect labour shortages. Accommodation and Wi-Fi provision depend on farm finances and unused facilities. Organic and GAP-certified farms offer lower wages, likely due to higher production costs, despite producing value-added goods. As platform-based paid volunteer tourism meets the needs of both farmers and volunteers, its prevalence is expected to increase. Full article

Wi-Fi router security is a real concern for universities and research centers that rely on strong, dependable networks for everything they do. In this study, we took a close look at four popular Wi-Fi router firmwares using open-source tools such as Binwalk, CVE-Bin-Tool, and Semgrep. We carefully examined the file systems, cross-referenced them with the National Vulnerability Database (NVD), and searched for outdated software like BusyBox and OpenSSL. What we found was clear: proprietary firmwares had more Critical and High vulnerabilities, while OpenWrt stood out for being more secure, easier to update, and openly maintained by its community. Our reproducible process automates how we gather evidence and map vulnerabilities, making firmware auditing more practical and trustworthy. These results make a strong case for using open-source firmware as a safer, more manageable choice for institutional networks. Full article

Mobile technologies are rapidly growing and shaping the tourism industry. Nonetheless, remote locations have specific characteristics that could restrain the deployment and use of technologies and jeopardize the sense of safety, affecting tourism experiences. There is a lack of empirical research that studies the importance of mobile technologies and security networks in remote destinations. A survey based on the Technology Acceptance Model (TAM) was conducted on 738 tourists during their stay in the Autonomous Region of the Azores, a nine-island Portuguese archipelago, to analyze the importance and impact of mobile technologies and security services. Since tourists have a high intensity of smartphone usage during their stay (86% use mobile internet and almost 50% use smartphones once per hour), mobile communication services and technologies need to be in place. Internet access and Wi-Fi are highly important for tourists for browsing and messaging, especially in urban areas, but also in rural and maritime areas. The availability of emergency and security networks is critical for destination selection and to engage in tourism activities. This paper contributes to the study of mobile tourism in remote destinations, with inputs regarding tourists’ behavior, and has implications for governance and industry stakeholders regarding destination management and the creation of meaningful and sustainable experiences with a high value for digital and smart tourists in the post-pandemic era. Full article

Cybersecurity in radio frequency (RF) technologies has become a critical concern, driven by the expansion of connected systems in urban and industrial environments. Although research on wireless networks and the Internet of Things (IoT) has advanced, comprehensive studies that provide a global and integrated view of cybersecurity development in this field remain limited. This work presents a scientometric and systematic review of international publications from 2009 to 2025, integrating the PRISMA protocol with semantic screening supported by a Large Language Model to enhance classification accuracy and reproducibility. The analysis identified two interdependent axes: one focusing on signal integrity and authentication in GNSS systems and cellular networks; the other addressing the resilience of IoT networks, both strongly associated with spoofing and jamming, as well as replay, relay, eavesdropping, and man-in-the-middle (MitM) attacks. The results highlight the relevance of RF cybersecurity in securing communication infrastructures and expose gaps in widely adopted technologies such as RFID, NFC, BLE, ZigBee, LoRa, Wi-Fi, and unlicensed ISM bands, as well as in emerging areas like terahertz and 6G. These gaps directly affect the reliability and availability of IoT and wireless communication systems, increasing security risks in large-scale deployments such as smart cities and cyber–physical infrastructures. Full article

Applications of smart cities, smart buildings, smart agriculture systems, smart grids, and other smart systems benefit from Internet of Things (IoT) protocols, networks, and architecture. Wireless Sensor Networks (WSNs) in smart systems that employ IoT use wireless communication technologies between sensors in the Things layer and the Fog layer hub. Such wireless protocols and networks include WiFi, Bluetooth, and Zigbee, among others. However, the payload formats of these protocols are heterogeneous, and thus, they lack a unified frame format that ensures interoperability. In this paper, a lightweight, interoperable frame format for low-rate, small-size Wireless Sensor Networks (WSNs) in IoT-based systems is designed, implemented, and tested. The practicality of this system is underscored by the development of a gateway that transfers collected data from sensors that use the unified frame to online servers via message queuing and telemetry transport (MQTT) secured with transport layer security (TLS), ensuring interoperability using the JavaScript Object Notation (JSON) format. The proposed frame is tested using market-available technologies such as Bluetooth and Zigbee, and then applied to smart home applications. The smart home scenario is chosen because it encompasses various smart subsystems, such as healthcare monitoring systems, energy monitoring systems, and entertainment systems, among others. The proposed system offers several advantages, including a low-cost architecture, ease of setup, improved interoperability, high flexibility, and a lightweight frame that can be applied to other wireless-based smart systems and applications. Full article

The Global Positioning System (GPS) and Received Signal Strength Indicator (RSSI) usage for location provenance often fails in obstructed, noisy, or densely populated urban environments. This study proposes a passive location provenance method that uses the location’s acoustics and the device’s acoustic side channel to address these limitations. With the smartphone’s internal microphone, we can effectively capture the subtle vibrations produced by the capacitors within the voltage-regulating circuit during wireless transmissions. Subsequently, we extract key features from the resulting audio signals. Meanwhile, we record the RSSI values of the WiFi access points received by the smartphone in the exact location of the audio recordings. Our analysis reveals a strong correlation between acoustic features and RSSI values, indicating that passive acoustic emissions can effectively represent the strength of WiFi signals. Hence, the audio recordings can serve as proxies for Radio-Frequency (RF)-based location signals. We propose a location-provenance framework that utilizes sound features alone, particularly the Mel-Frequency Cepstral Coefficients (MFCCs), achieving coarse localization within approximately four kilometers. This method requires no specialized hardware, works in signal-degraded environments, and introduces a previously overlooked privacy concern: that internal device sounds can unintentionally leak spatial information. Our findings highlight a novel passive side-channel with implications for both privacy and security in mobile systems. Full article

Over-the-air (OTA) firmware updating has become a fundamental requirement in modern Internet of Things (IoT) deployments, where thousands of heterogeneous embedded devices operate in remote and distributed environments. Manual firmware maintenance in such systems is impractical, costly, and prone to security risks, making automated update mechanisms essential for long-term reliability and lifecycle management. This paper presents a unified OTA update architecture for ESP32-based IoT devices that integrates centralized version control and multi-protocol communication support (Wi-Fi, BLE, Zigbee, LoRa, and GSM), enabling consistent firmware distribution across heterogeneous networks. The system incorporates version-compatibility checks, rollback capability, and a server-driven release routing mechanism for development and production branches. An analytical model of timing, reliability, and energy consumption is provided, and experimental validation on a fleet of ESP32 devices demonstrates reduced update latency compared to native vendor OTA solutions, together with reliable operation under simultaneous device loads. Overall, the proposed solution provides a scalable and resilient foundation for secure OTA lifecycle management in smart-industry, remote sensing, and autonomous infrastructure applications. Full article

The fast expansion of the Internet of Things (IoT) has accelerated the advancement of smart home technologies. However, secure communication and access control remain significant challenges. This paper presents a fully implemented FPGA-based IoT gateway that utilizes the Zynq-7000 SoC, integrating sensing, processing, wireless communication, and hardware-level authentication. Analog temperature data from an LM35 sensor is digitized via a 12-bit XADC and transmitted over Wi-Fi using an ESP8266-01 module. An SPI-based OLED provides real-time feedback. To ensure device-level trust, an XOR-based Physically Unclonable Function (PUF) enables lightweight challenge–response authentication with over good uniqueness and a latency of under 10 ms. The system demonstrates ±0.5 °C sensing accuracy, <50 ms transmission delay, and low power consumption. It offers a scalable and secure platform suitable for real-time smart home and facility automation. Full article

Integrating IoT devices into smart grids raises some hard problems related to safe data sharing, the ability to grow, and energy use. Blockchain provides a safe way to check identities without a central authority. Typical ways to confirm transactions, like Proof-of-Work (PoW), use a lot of power, making them bad for devices that cannot use much energy. This study introduces a safe authentication system using Blockchain, a Deep Neural Network (DNN), and a power-saving way to confirm transactions (EACM). The system picks validators based on how much power they have left and their trust scores to save power during confirmation. Using the IoT-Enabled Smart Grid Dataset, simulations showed a transaction speed of 372 TPS, which is 32% better than normal methods. The system correctly authenticates 98.69% of the time, with a confirmation delay of 5.9 milliseconds and an 18% drop in validator node energy use. Also, the system spots 98.4% of unauthorized access tries, with a false acceptance rate (FAR) of 1.7% and a false rejection rate (FRR) of 0.31%. These outcomes prove the system’s ability to offer safe, fast, and energy-saving authentication for big, real-time Smart Grid IoT setups. Full article

Secure authentication in vehicular ad hoc networks (VANETs) remains a fundamental challenge due to their dynamic topology, susceptibility to attacks, and scalability constraints in multi-hop communication. Existing approaches based on elliptic curve cryptography (ECC), blockchain, and fog computing have achieved partial success but suffer from latency, resource overhead, and limited adaptability, leaving a gap for lightweight and hardware-rooted trust models. To address this, we propose a multi-hop mutual authentication protocol leveraging Physical Unclonable Functions (PUFs), which provide tamper-evident, device-specific responses for cryptographic key generation. Our design introduces a structured sequence of phases, including pre-deployment, registration, login, authentication, key establishment, and session maintenance, with optional multi-hop extension through relay vehicles. Unlike prior schemes, our protocol integrates fuzzy extractors for error tolerance, employs both inductive and game-based proofs for security guarantees, and maps BAN-logic reasoning to specific attack resistances, ensuring robustness against replay, impersonation, and man-in-the-middle attacks. The protocol achieves mutual trust between vehicles and RSUs while preserving anonymity via temporary identifiers and achieving forward secrecy through non-reused CRPs. Conceptual comparison with state-of-the-art PUF-based and non-PUF schemes highlights the potential for reduced latency, lower communication overhead, and improved scalability via cloud-assisted CRP lifecycle management, while pointing to the need for future empirical validation through simulation and prototyping. This work not only provides a secure and efficient solution for VANET authentication but also advances the field by offering the first integrated taxonomy-driven evaluation of PUF-enabled V2X protocols in multi-hop Wi-Fi environments. Full article

Private fifth generation (5G) networks have emerged as a cornerstone for ultra-reliable, low-latency connectivity across mission-critical domains such as industrial automation, healthcare, and smart cities. Compared to conventional technologies like 4G or Wi-Fi, they provide clear advantages, including enhanced service continuity, higher reliability, and customizable security controls. However, these benefits come with new security challenges, particularly regarding the confidentiality, integrity, and availability of data and services. This article presents a review of security vulnerabilities in private 5G networks. The review pursues four objectives: (i) to identify and categorize key vulnerabilities, (ii) to analyze threats that undermine core security principles, (iii) to evaluate mitigation strategies proposed in the literature, and (iv) to outline gaps that demand further investigation. The findings offer a structured perspective on the evolving threat landscape of private 5G networks, highlighting both well-documented risks and emerging concerns. By mapping vulnerabilities to mitigation approaches and identifying areas where current solutions fall short, this study provides critical insights for researchers, practitioners, and policymakers. Ultimately, the review underscores the urgent need for robust and adaptive security frameworks to ensure the resilience of private 5G deployments in increasingly complex and high-stakes environments. Full article