Search Results (2,251)

Stroke continues to impose an enormous morbidity and mortality burden worldwide. Stroke survivors often incur debilitating consequences that impair motor function, independence in activities of daily living and quality of life. Rehabilitation is a pivotal intervention to minimize disability and promote functional recovery following a stroke. The Internet of Medical Things, a network of connected medical devices, software and health systems that collect, store and analyze health data over the internet, is an emerging resource in neurorehabilitation for stroke survivors. Technologies such as asynchronous transmission to handle intermittent connectivity, edge computing to conserve bandwidth and lengthen device life, functional interoperability across platforms, security mechanisms scalable to resource constraints, and hybrid architectures that combine local processing with cloud synchronization help bridge the digital divide and infrastructure limitations in low-resource environments. This manuscript reviews emerging rehabilitation technologies such as robotic devices, virtual reality, brain–computer interfaces and telerehabilitation in the setting of neurorehabilitation for stroke patients. Full article

Visual secret sharing (VSS) schemes can enhance the security of image transmission over networks. Conventional VSS schemes often generate meaningless shares, which can raise suspicion among potential attackers. To address this issue, this paper proposes a novel VSS scheme that integrates information hiding techniques with quick response (QR) codes to generate meaningful shares. The first $n-1$ shares are encoded as standard QR codes, while the n-th share is embedded into a grayscale carrier image using a reversible information hiding method, ensuring the carrier remains visually meaningful. During transmission, the $n-1$ QR codes and the hidden image are distributed. At the receiver end, the hidden n-th share is extracted losslessly from the carrier image using the $n-1$ QR codes, and the original secret image is perfectly reconstructed by bitwise XORing all n shares. Experimental results demonstrate the feasibility, security, and visual quality of the proposed scheme. Full article

With the development of mobile crowdsensing systems (MCSs), wireless network transmission efficiency has attracted widespread attention. Network coding can be used in wireless communication to improve network throughput and robustness, which allows intermediate nodes to perform arbitrary coding operations on data packets. However, the data packet in network coding systems is vulnerable to pollution attacks. The special operation of intermediate nodes makes some security protocols in traditional store-and-forward networks unavailable in network coding systems. To address this problem, an efficient certificate-based linearly homomorphic signature scheme against pollution attacks in network coding systems is presented. A novel homomorphic contraction mapping technique is introduced to reduce the computational cost of signature generation. In the proposed scheme, the computational cost of both signature generation and verification is independent of the data packet size. Furthermore, a construction is provided to simultaneously defend against both eavesdropping attacks and pollution attacks in unicast networks. The security of the certificate-based linearly homomorphic signature scheme is formally proved in the random oracle model (ROM), and the scheme is implemented using the Java Pairing-Based Cryptography (JPBC) library. Simulation results demonstrate that the scheme is efficient and practical for real-world deployments in public environments without requiring secure channels. Full article

With the rapid development of Internet of Things (IoT) and Artificial Intelligence (AI) technologies, information security has become a critical issue. To develop a highly secure image encryption transmission system, this study proposes a novel key generation mechanism based on the combination of fractional-order chaotic system synchronization control and the SHA-256 algorithm. This proposed method dynamically generates high-quality synchronous random number sequences and is combined with the Advanced Encryption Standard (AES) algorithm. To quantitatively evaluate the mechanism, the generated sequences are tested using NIST SP 800-22, ENT, and DIEHARD suites. The comparative results show that the key generation mechanism produces sequences with higher randomness and unpredictability. In the evaluation of image encryption, histogram distribution, information entropy, adjacent pixel correlation, NPCR, and UACI are used as performance metrics. Experimental results show that the histogram distributions are uniform, the values of information entropy, NPCR, and UACI are close to their ideal levels, and the pixel correlation is significantly reduced. Compared to recent studies, the proposed method demonstrates higher encryption performance and stronger resistance to statistical attacks. Furthermore, the system effectively addresses key distribution and management problems inherent in traditional symmetric encryption schemes. These results validate the reliability and practical feasibility of the proposed approach. Full article

Wireless sensor networks comprise many resource-constrained nodes that must protect both local readings and routing metadata. The sensors collect data from the environment or from the individual to whom they are attached and transmit it to the nearest gateway node via a wireless network for further delivery to external users. Due to wireless communication, the transmitted messages may be intercepted, rerouted, or even modified by an attacker. Consequently, security and privacy issues are of utmost importance, and the nodes must be protected against unauthorized access during transmission over a public wireless channel. To address these issues, we propose the Probabilistic Bit-Similarity-Based Key Agreement Protocol (PBS-KAP). This novel method enables two nodes to iteratively converge on a shared secret key without transmitting it or relying on pre-installed keys. PBS-KAP enables two nodes to agree on a symmetric session key using probabilistic similarity alignment with explicit key confirmation (MAC). Optimized Garbled Circuits facilitate secure computation with minimal computational and communication overhead, while Secure Sketches combined with Fuzzy Extractors correct residual errors and amplify entropy  producing reliable and uniformly random session keys. The resulting protocol provides a balance between security, privacy, and usability, standing as a practical solution for real-world WSN and IoT applications without imposing excessive computational or communication burdens. Security relies on standard computational assumptions via a one-time elliptic–curve–based base Oblivious Transfer, followed by an IKNP Oblivious Transfer extension and a small garbled threshold circuit. No pre-deployed long-term keys are required. After the bootstrap, only symmetric operations are used. We analyze confidentiality in the semi-honest model. However, entity authentication, though feasible, requires an additional Authenticated Key Exchange step or malicious-secure OT/GC. Under the semi-honest OT/GC assumption, we prove session-key secrecy/indistinguishability; full entity authentication requires an additional AKE binding step or malicious-secure OT/GC.  Full article

Against the backdrop of global warming and an increase in extreme weather events, the freshwater aquaculture industry, which is highly dependent on environmental conditions, faces severe challenges. As the world’s largest producer of freshwater aquaculture, the stability of China’s production is crucial for ensuring national food security and rural livelihoods. This study utilizes provincial panel data from China (2007–2023) and employs the HP filter separately for each province to construct a “climate-induced output” indicator. A panel data model is then established to examine the impact and transmission mechanisms of extreme climate risks on freshwater aquaculture output. The findings reveal the following: (1) Climate risks exert a significant negative impact on freshwater aquaculture production, with extreme low temperatures, droughts, and extreme rainfall having particularly pronounced effects. (2) Natural disasters play a partial mediating role between extreme climate and output, accounting for approximately 26.35% of the total effect. (3) From an overall perspective, both increased labor productivity and greater operational scale can significantly mitigate the negative impacts of climate risks. This study provides empirical evidence to inform policies on optimizing regional aquaculture layouts, enhancing climate resilience, and formulating adaptive strategies. Full article

Due to increasing human activities underwater, there is a growing demand for high-speed underwater optical communication (UOWC) data links for security surveillance, environmental monitoring, pipeline inspection, and other applications. Line-of-sight communication is impossible under certain conditions due to misalignment, physical obstructions, irregular usage, and difficulty adjusting the receiver orientation, especially when used in environments with mobile users or submerged sensor networks. Therefore, non-line-of-sight (NLOS) optical communication is used in this study. Advanced modulation schemes—quadrature amplitude modulation and orthogonal frequency-division multiplexing (QAM-OFDM)—were used to transmit the signal underwater between two network nodes. QAM increases the data transfer rate, while OFDM reduces dispersion and inter-symbol interference (ISI). The proposed UOWC system is investigated using a 532 nm green laser diode (LD). Reliable high-speed data transmission of up to 15 Gbps is achieved over horizontal distances of 134 m, 43 m, 21 m, and 5 m in four different aquatic environments—pure water (PW), clear ocean (CLO), coastal ocean (COO), and harbor II (HarII), respectively. The system achieves effectively error-free performance within the simulation duration (BER < 10⁻⁹), with a received optical signal power of approximately −41.5 dBm. Clear constellation patterns and low BER values are observed, confirming the robustness of the proposed architecture. Despite the limitations imposed by non-line-of-sight (NLOS) communication and the diversity aquatic environments, our proposed architecture excels at underwater long-distance data transmission at high speeds. Full article

Linear array detector-based infrared push-broom imaging systems are widely employed in remote sensing and security surveillance due to their high spatial resolution, wide swath coverage, and low cost. However, the massive data volume generated during continuous scanning presents substantial storage and transmission challenges. To mitigate this issue, we propose a lossless compression algorithm based on pixel-adaptive prediction and hierarchical decomposition of residuals. The algorithm first performs pixel-wise adaptive noise compensation according to local image characteristics and achieves efficient prediction by exploiting the strong inter-pixel correlation along the scanning direction. Subsequently, hierarchical decomposition is applied to high-energy residual blocks to further eliminate spatial redundancy. Finally, the Golomb–Rice coding parameters are adaptively adjusted based on the neighborhood residual energy, optimizing the overall code length distribution. The experimental results demonstrate that our method significantly outperforms most state-of-the-art approaches in terms of both the compression ratio (CR) and bits per pixel (BPP). Moreover, while maintaining a CR comparable to H.265-Intra, our method achieves a 21-fold reduction in time complexity, confirming its superiority for large-format image compression. Full article

As the digitalization and intelligent transformation of power systems accelerates, the Power Internet of Things (PIoT) plays a pivotal role in ensuring efficient energy transmission and real-time regulation. However, this openness and interconnectivity also expose the system to diverse cyber threats, where attackers can disrupt stable power communication and dispatch operations through means such as data tampering, denial-of-service attacks, and control intrusion. To characterize the dynamic adversarial process between attackers and defenders in the PIoT, this paper constructs a zero-sum differential game model for cyber attack–defense strategy selection. To achieve equilibrium in the formulated differential game, optimal control theory is employed to solve the optimization problems of the game participants, thereby deriving the optimal strategies for both attackers and defenders. Finally, simulation results illustrate the evolution of network resource competition between attackers and defenders in the PIoT. The results also demonstrate that our proposed model can effectively and accurately describe the evolution of the system security state and the impact of strategic interactions between attackers and defenders. Full article

In the era of big data and multimedia communication, securing color images against unauthorized access and attacks is a pressing challenge. While quaternion-based models provide a unified representation for color images, most existing encryption schemes rely on single-image frameworks or lack the mathematical rigor to ensure both security and feasibility. To bridge this gap, this paper introduces a system of generalized Sylvester-type quaternion matrix equations as a novel encryption model. By using the equivalence canonical forms of five matrices arranged in a specific array, we provide necessary and sufficient conditions for the solvability of the generalized Sylvester-type quaternion matrix equation system, depending on the rank of the coefficient matrix. Numerical examples are provided to validate the obtained results. As an example of applications, we develop an encryption scheme for color images based on the proposed quaternion matrix equation system. Experimental results confirm the high feasibility of the proposed scheme. Notably, the proposed model supports dynamic key updates and multi-image secure transmission, making it highly adaptable for real-world applications. By integrating advanced quaternion matrix theory with practical image encryption, this work offers a scalable, secure, and mathematically sound approach to color image protection. Full article

The widespread use of low-cost, highly maneuverable unmanned aerial vehicles (UAVs), such as racing drones, has raised numerous security concerns. These UAVs commonly employ LoRa (Long Range) communication protocols, which feature long-range transmission and strong anti-interference capabilities. However, traditional countermeasure techniques targeting LoRa-based links often suffer from delayed response, poor adaptability, and high power consumption. To address these challenges, this study first leverages neural networks to achieve efficient detection and reverse extraction of key parameters from LoRa signals in complex electromagnetic environments. Subsequently, a continuous preamble injection jamming method is designed based on the extracted target signal parameters. By protocol-level injection, this method disrupts the synchronization and demodulation processes of UAV communication links, significantly enhancing jamming efficiency while reducing energy consumption. Experimental results demonstrate that, compared with conventional approaches, the proposed continuous preamble injection jamming method achieves improved signal detection accuracy, jamming energy efficiency, and effective range. To the best of our knowledge, this protocol-aware scheme, which integrates neural network-based signal perception and denoising, offers a promising and cost-effective technical pathway for UAV countermeasures. Full article

The broadcast nature of wireless channels introduces significant security vulnerabilities in information transmission, particularly when the eavesdropper is close to the legitimate destination. In such scenarios, the eavesdropping channel often exhibits high spatial correlation with, or even superior quality to, the legitimate channel. This makes it challenging for traditional power optimization methods to effectively suppress the eavesdropping rate. To address this challenge, this paper proposes an optimization method for the secrecy capacity of unmanned aerial vehicle (UAV) relaying based on the dynamic adjustment of the power allocation factor. By injecting artificial noise (AN) during signal forwarding and combining it with real-time channel state information, the power allocation factor can be dynamically adjusted to achieve precise jamming of the eavesdropping link. We consider a four-node communication model consisting of a source, a UAV, a legitimate destination, and a passive eavesdropper, and formulate a joint optimization problem to maximize the secrecy rate. Due to the non-convexity of the original problem, we introduce relaxation variables and apply successive convex approximation (SCA) to reformulate it into an equivalent convex optimization problem. An analytical solution for the power allocation factor is derived using the water-filling (WF) algorithm. Furthermore, an alternating iterative optimization algorithm with AN assistance is proposed to achieve global optimization of the system parameters. Simulation results demonstrate that, compared to traditional power optimization schemes, the proposed algorithm substantially suppresses the eavesdropping channel capacity while enhancing transmission efficiency, thereby significantly improving both secrecy performance and overall communication reliability. Full article

Intelligent vehicle networks powered by machine learning, AI and blockchain are transforming various sectors beyond transportation. In this context, being able to remote drive a vehicle is key for enhancing autonomous driving systems. After deploying end-to-end teleoperated driving systems under 5G networks, the need to address complex challenges in other critical areas arises. These challenges belong to different technologies that need to be integrated in this particular system: video transmission and visualization technologies, artificial intelligence techniques, and network optimization features, incorporating haptic devices and critical data security. This article explores how these technologies can enhance the teleoperated driving activity experiences already executed in real-life environments by analyzing the quality of the video which is transmitted over the network, exploring its correlation with the current state-of-the-art AI object detection algorithms, analyzing the extended reality and digital twin paradigms, obtaining the maximum possible performance of forthcoming 6G networks and proposing decentralized security schema for ensuring the privacy and safety of the end-users of teleoperated driving infrastructures. An integrated set of conclusions and recommendations will be given to outline the future teleoperated driving systems design in the forthcoming years. Full article

The Internet of Military Things (IoMT) relies on Long-Range Wide Area Networks (LoRaWAN) for low-power, long-range communication in critical applications like border security and soldier health monitoring. However, conventional priority-based flow control mechanisms, which rely on static classification thresholds, lack the adaptability to handle the nuanced, continuous nature of physiological data and dynamic network states. To overcome this rigidity, this paper introduces a novel, domain-adaptive Fuzzy Logic Flow Control (FFC) protocol specifically tailored for LoRaWAN-based IoMT. While employing established Mamdani inference, the FFC system innovatively fuses multi-parameter physiological data (body temperature, blood pressure, oxygen saturation, and heart rate) into a continuous Health Score, which is then mapped via a context-optimised sigmoid function to dynamic transmission intervals. This represents a novel application-layer semantic integration with LoRaWAN’s constrained MAC and PHY layers, enabling cross-layer flow optimisation without protocol modification. Simulation results confirm that FFC significantly enhances reliability and energy efficiency while reducing latency relative to traditional static priority architectures. Seamlessly integrated into the NS-3 LoRaWAN simulation framework, the FFC protocol demonstrates superior performance in IoMT communications. Simulation results confirm that FFC significantly enhances reliability and energy efficiency while reducing latency compared with traditional static priority-based architectures. It achieves this by prioritising high-priority health telemetry, proactively mitigating network congestion, and optimising energy utilisation, thereby offering a robust solution for emergent, health-critical scenarios in resource-constrained environments. Full article

With the widespread diffusion of personal Internet of Things (IoT) devices, Electromagnetic Side-Channel Attacks (EM-SCAs), which exploit electromagnetic emissions to uncover critical data such as cryptographic keys, are becoming extremely common. Existing shielding approaches typically rely on bulky or opaque materials, which limit integration in modern IoT environments; this motivates the need for a transparent, lightweight, and easily integrable solution. Thus, to address this threat, we propose the use of electromagnetic metasurfaces with shielding capabilities, fabricated with an optically transparent conductive film. This film can be easily integrated into glass substrates, offering a novel and discrete shielding solution to traditional methods, which are typically based on opaque dielectric media. The paper presents two proof-of-concept case studies for shielding against EM-SCAs. The first one investigates the design and fabrication of a passive metasurface aimed at shielding emissions from chip processors in IoT devices. The metasurface is conceived to attenuate a specific frequency range, characteristic of the considered IoT processor, with a target attenuation of 30 dB. At the same time, the metasurface ensures that signals from 4G and 5G services are not affected, thus preserving normal wireless communication functioning. Conversely, the second case study introduces an active metasurface for dynamic shielding/transmission behavior, which can be modulated through diodes according to user requirements. This active metasurface is designed to block undesired electromagnetic emissions within the 150–465 MHz frequency range, which is a common band for screen gleaning security threats. The experimental results demonstrate an attenuation of approximately 10 dB across the frequency band when the shielding mode is activated, indicating a substantial reduction in signal transmission. Both the case studies highlight the potential of transparent metasurfaces for secure and dynamic electromagnetic shielding, suggesting their discrete integration in building windows or other environmental structural elements. Full article