Recent advances in electronic devices and communication infrastructure have revolutionized the traditional healthcare system into a smart by using internet of medical things (IoMT) devices. However, due to centralized training approach artificial intelligence (AI), mobile wearable IoMT raise privacy issues concerning information communicated between hospitals end-users. The conveyed is highly confidential can be exposed adversaries. In this regard, federated learning (FL), distributive AI...

Digital twin (DT) provides accurate guidance for multidimensional resource scheduling in 5G edge computing-empowered distribution grids by establishing a digital representation of the physical entities. In this article, we address critical challenges DT construction and DT-assisted such as low accuracy, large iteration delay, security threats. We propose federated learning-based framework present Secure lAtency-aware dIgital assisted scheduliNg algoriThm (SAINT). SAINT achieves low-latency,...

Vehicle to vehicle (V2V) communication has gained importance in recent times because of the increasing number traffic accidents and advancements information sharing. A secure reliable data transfer become important ensure safety trust vehicular network users. Because scalability V2V communication, proposed solutions must have low computational complexities free from latency issues. In this paper, we utilize channel characteristics wireless networks which are used generate link fingerprints....

Epilepsy is the most unpredictable and recurrent disease among neurological diseases. Early detection of epileptic seizures can play a critical role in providing timely treatment to patients especially when patient remote area. This paper uses deep learning framework detect epilepsy Electroencephalography (EEG) signal. The dataset used publicly available has recording three kinds EEG signals: pre-ictal, inter-ictal (seizure-free epileptic) ictal (epileptic with seizure). proposed Long...

While operating in three different modes with bi-directional power flow, electricity theft detection, and localization a grid-tied microgrid (MG) become challenging tasks, particularly when the occurrence rate of its frequency patterns are random. To address this problem, stochastic Petri net formalism is used paper to detect localize MGs. The disturbance at any instance time form resistance above threshold accumulated data smart meter, irrespective mode operation, triggers transition...

Next-generation wireless communication and networking technologies, such as sixth-generation (6G) networks software-defined Internet of Things (SDIoT), make cyber-physical systems (CPSs) more vulnerable to cyberattacks. In massively connected CPSs, an intruder can trigger a cyberattack in the form false data injection, which lead system instability. To address this issue, we propose graphics-processing-unit-enabled adaptive robust state estimator. It comprises deep learning algorithm, long...

For optimal utilization of power generation resources, load forecasting plays a vital role in balancing the flow distribution network. There are several drawbacks associated with existing techniques for balancing. Neural network (NN) based unable to consider actual states system, while weighted least squares state estimation (WLS) fails counter nonlinearity demand profile. In this article, hybrid approach is proposed short term forecasting. The technique, comprised WLS, NN, and adaptive...

Age of information (AoI) is an important metric timeliness, which determines digital twin (DT) consistency and energy management precision. However, AoI guarantee in the time-averaged sense unreliable to avoid occurrence extreme event. In this paper, we propose a novel timeliness named ultra-low (ULAoI). Compared with AoI, ULAoI further considers event higher-order statistical characteristics excess value. Multi-dimensional resources power internet things (PIoT) are jointly allocated achieve...

Due to the limited resources and scalability, security protocols for Internet of Things (IoT) need be light-weighted. The cryptographic solutions are not feasible apply on small low-energy devices IoT because their energy space limitations. In this paper, a light-weight protocol secure data achieving provenance is presented multi-hop network. Received Signal Strength Indicator (RSSI) communicating nodes used generate link fingerprints. fingerprints matched at server compute correlation...

The traditional Internet architecture relies on the best-effort principle, which is not suitable for critical industrial of Things (IIoT) applications such as healthcare systems with stringent quality-of-service (QoS) requirements. In this article, a software-defined network (SDN) based an analytical parallel routing framework proposed by using massive processing power graphics unit (GPU) dynamically optimizing multiconstrained QoS parameters in IIoT. considers three types smart traffic:...

Multipath Transmission Control Protocol (MPTCP) enables multi-homed devices to establish multiple simultaneous routes for data transmission. Congestion (CC) is a fundamental mechanism implementing and designing MPTCP. The Internet of Things (IoT) networks generate massive volume heterogeneous traffic with high dimensional states diverse QoS characteristics. existing MPTCP CC algorithms are unable perform efficiently under highly mobile dynamic IoT environments. We propose novel model-free...

Space-assisted vehicular networks (SAVN) provide seamless coverage and on-demand data processing services for user vehicles (UVs). However, ultra-reliable low-latency communication (URLLC) demands imposed by emerging applications are hard to be satisfied in SAVN existing computation offloading techniques. Traditional deep reinforcement learning algorithms unsuitable highly dynamic due the underutilization of environment observations. An AsynchronouS federaTed Q-learning (DQN)-basEd...

The rapid growth of electric vehicle (EV) penetration has led to more flexible and reliable vehicle-to-grid-enabled cyber-physical systems (V2G-CPSs). However, the increasing system complexity also makes them vulnerable threats. Coordinated cyber attacks (CCAs) have emerged as a major concern, requiring effective detection mitigation strategies within V2G-CPSs. Digital twin (DT) technologies shown promise in mitigating providing diverse functionalities for complex tasks such monitoring,...

Intelligent Transportation Systems (ITSs) comprise a whole infrastructure of conventional vehicles, Connected Autonomous Vehicles (CAVs), roadside units, and communication equipment. As result, variety smart sensors, cloud, edge services are used. Due to the Vehicle-to-Everything (V2X) involved in these, becomes prone security attacks. The most common these is False Data Injection Attack (FDIA), which causes serious consequences upon driving decisions CAV. Blockchain an ascending technology...

Short Time Fourier Transform (STFT) is an important technique for the time-frequency analysis of a time varying signal. The basic approach behind it involves application Fast (FFT) to signal multiplied with appropriate window function fixed resolution. selection size difficult when no background information about input known. In this paper, novel empirical model proposed that adaptively adjusts narrow band-signal using spectrum sensing technique. For wide-band signals, where resolution...

Energy efficient object detection and image transmission are one of the key issues in wireless multimedia sensor networks (WMSN). Recent approaches WMSN propose in-node tracking algorithms. However, a little effort has been made to effectively detect presence absence images WMSN. Since direct relation with transmission, therefore effective algorithm would provide reduction false information. In this paper, novel model an scheme proposed for This uses segments rather than complete image. It...

The protection of smart meters (SMs) from cyberattacks is utmost importance because SMs in advanced metering infrastructure (AMI) are physically unprotected and produce a large amount sensitive data. Due to scalability, the small-sized low-cost devices having low computational capabilities. algorithms that designed complete security requirements should be lightweight. To address this issue, paper proposes lightweight solution man-in-the-middle attack, data tempering, blockchain-based...

The Artificial Intelligence-enabled Internet of Medical Things (AI-IoMT) envisions the connectivity medical devices encompassing advanced computing technologies to empower large-scale intelligent healthcare networks. AI-IoMT continuously monitors patients' health and vital computations via IoMT sensors with enhanced resource utilization for providing progressive care services. However, security concerns these autonomous systems against potential threats are still underdeveloped. Since sensor...

Effectively managing network resources in the complex and ever-evolving realms of Internet Things (IoT) ecosystems presents a formidable challenge. Conventional resource allocation methods often grapple with adapting to dynamic nature IoT environments, resulting suboptimal performance delayed responsiveness. The advent stateof-the-art technologies, notably intelligent reflecting surfaces (IRSs), further amplifies complexity, particularly optimizing IRS configurations within networks. To...

The current landscape of data-centric Internet Vehicles (IoVs) encompasses a fusion Human-driven (HVs), Autonomous (AVs), Road-Side Units (RSUs), and edge-based devices engaged in periodic communication. Given the stringent latency requirements inherent vehicular communications, emergence Digital Twins (DTs) plays pivotal role problem-solving, ensuring rapid response, regulatory compliance, seamless availability. While these communications serve as backbone IoV, they also create an opportune...