Decentralized applications (DApps) have developed rapidly owing to their censorship resistance, user autonomy, and distributed architecture. However, privacy and regulatory restrictions can limit access to representative traffic samples, while class...
Diffusion models have been widely used in image generation and structured trajectory generation. DPM++ samplers improve few-step inference by recursively propagating current and historical denoised states, but their behavior in the low-noise regime r...
Most machine learning algorithms only have a good recognition rate on balanced datasets. However, in the field of malicious traffic identification, benign traffic on the network is far greater than malicious traffic, and the network traffic dataset i...
For urban traffic, traffic accidents are the most direct and serious risk to people’s lives, and rapid recognition and warning of traffic accidents is an important remedy to reduce their harmful effects. However, research scholars are often confronte...
In recent years, with the rapid development of Internet services in all walks of life, a large number of malicious acts such as network attacks, data leakage, and information theft have become major challenges for network security. Due to the difficu...
With the popularization of IoT (Internet of Things) devices and the continuous development of machine learning algorithms, learning-based IoT malicious traffic detection technologies have gradually matured. However, learning-based IoT traffic detecti...
Traffic loads are the primary external loads on bridges during their service life. However, an accurate analysis of the long-term effect of the operating traffic load is difficult because of the diversity of traffic flow in terms of vehicle type and...
Network traffic generation technology plays a critical role in network testing and security protection. It simulates various network traffic patterns, offering intrusion detection systems with diverse samples. These samples enhance the system’s...
With the rapid development of the Internet of Things (IoT) and the increase in the frequency of cyberattacks, accurate identification of IoT end devices is critical to their security. Existing identification methods are based on raw, statistical, and...
A substantial amount of money and time is required to optimize resources in a massive Wi-Fi network in a real-world environment. Therefore, to reduce cost, proposed algorithms are first verified through simulations before implementing them in a real-...
With the proliferation of mobile terminals and the rapid growth of network applications, fine-grained traffic identification has become increasingly challenging. Methods based on machine learning and deep learning have achieved remarkable results, bu...
With the development and widespread application of network information, new technologies led by 5G are emerging, resulting in an increasingly complex network security environment and more diverse attack methods. Unlike traditional networks, 5G networ...
Traffic accidents at urban intersections may lead to severe traffic congestion, necessitating effective detection and timely intervention. To achieve real-time traffic accident monitoring at intersections more effectively, this paper proposes an urba...
Microscopic traffic flow data, an important input to virtual test scenarios for autonomous driving, are often difficult to obtain in large quantities to allow for batch testing. In this paper, a neural network for generating microscopic traffic flow...
A large amount of sensitive information is generated in today’s evolving network environment. Some hackers utilize low-frequency attacks to steal sensitive information from users. This generates minority attack samples in real network traffic....
A SDN (Software-Defined Network) separates the control layer from the data layer to realize centralized network control and improve the scalability and the programmability. SDN also faces a series of security threats. An intrusion detection system (I...
Highway ramp merging requires autonomous vehicles to make safe and efficient decisions in dense mixed traffic, where strong vehicle interactions and rapidly changing acceptable gaps make the task particularly challenging. Existing reinforcement learn...
Portugal has the sixth highest road fatality rate among European Union members. This is a problem of different dimensions with serious consequences in people’s lives. This study analyses daily data from police and government authorities on road...
Considering the exponential growth of network traffic, particularly driven by over-the-top (OTT) streaming applications, video category network traffic constitutes a significant portion of overall network traffic. However, most research has focused o...
Wireless body area networks (WBANs) for healthcare monitoring require age-of-information (AoI)-aware resource allocation under heterogeneous periodic and aperiodic traffic. Existing AoI-aware resource allocation methods can be broadly divided into ce...
This study proposes ViTWGAN, a novel and effective intrusion detection model designed to enhance data privacy protection by detecting malicious traffic within network flows. By improving the discriminator’s loss function, our approach reduces b...
The rationality of heavy vehicle models is crucial to the structural safety assessment of bridges. To establish a realistic heavy vehicle traffic flow model, this study proposes a heavy vehicle random traffic flow simulation method that fully conside...
Reliable traffic-flow models are important for traffic analysis, simulation and intelligent transport management, yet fundamental traffic-flow relationships are frequently transferred between countries despite differences in road design, traffic comp...
In the last years of the past century, complex correlation structures were empirically observed, both in aggregated and individual traffic traces, including long-range dependence, large-timescale self-similarity and multi-fractality. The use of stoch...
Large hospitals in China typically face high-density patient flows, highly concentrated medical service demands, and significant impacts on surrounding transportation systems. To explore this issue in depth, this study selected a sample of 135 hospit...
Exposure to traffic-related air pollution (TRAP) generates oxidative stress, with downstream effects at the metabolic level. Human studies of traffic density and metabolomic markers, however, are rare. The main objective of this study was to evaluate...
In this paper, we propose a method for the generation of simulated test scenarios for autonomous driving. Based on the requirements of standard regulatory test scenarios, we can generate virtually simulated scenarios and functional scenario libraries...
The Internet of Things (IoT) continues to expand across critical infrastructures, enabling automation, efficiency, and data driven decision making; yet, reliable device identification from network traffic remains hampered by severe class imbalance th...
In network intrusion detection, class imbalance, the scarcity of minority-class attack samples, high feature dimensionality, and substantial feature redundancy are prevalent issues that limit the detection capability of intrusion detection models. To...
Traffic sign recognition is a classification problem that poses challenges for computer vision and machine learning algorithms. Although both computer vision and machine learning techniques have constantly been improved to solve this problem, the sud...
Accurately predicting the long-term trajectories of agents in complex traffic environments is crucial for the safety and effectiveness of autonomous driving systems. This paper introduces DBN-MACTraj, a probabilistic model that takes historical traje...
High-availability seamless redundancy (HSR) is a protocol for Ethernet networks that provides duplicated frames with zero recovery time in the event of any network component’s failure. It is suited for applications that demand high availability and a...
Traffic management and control applications require comprehensive knowledge of traffic flow data. Typically, such information is gathered using traffic sensors, which have two basic challenges: First, it is impractical or impossible to install sensor...
This study proposes an enhanced network intrusion detection model, 1D-TCN-ResNet-BiGRU-Multi-Head Attention (TRBMA), aimed at addressing the issues of incomplete learning of temporal features and low accuracy in the classification of malicious traffi...
To address the class imbalance issue in network intrusion detection, which degrades performance of intrusion detection models, this paper proposes a novel generative model called VAE-WACGAN to generate minority class samples and balance the dataset....
On-board vision systems may need to increase the number of classes that can be recognized in a relatively short period. For instance, a traffic sign recognition system may suddenly be required to recognize new signs. Since collecting and annotating s...
Small object detection in traffic sign applications often faces challenges like complex backgrounds, blurry samples, and multi-scale variations. Existing solutions tend to complicate the algorithms. In this study, we designed an efficient and simple...
The widespread use of the onion browser (Tor) has provided a breeding ground for the proliferation of cybercriminal activities and the Tor anonymous traffic identification method has been used to fingerprint anonymous web traffic and identify the web...
Simulation models of transport systems are a key tool for solving many problems in the field of management of these systems. The methodologies for creating such models use datasets on both transport infrastructure and demand for the delivery of goods...
The rising frequency of network intrusions has significantly impacted critical infrastructures, leading to an increased focus on the detection of malicious network traffic in recent years. However, traditional port-based and classical machine learnin...
Class imbalance remains a major obstacle to reliable network intrusion detection, particularly in Internet of Things (IoT) and sensor-network monitoring scenarios where rare attack categories are represented by only a small number of high-dimensional...
Website fingerprinting (WF) attacks analyze encrypted network traffic to exploit side-channel features such as packet sizes, inter-packet timings, and burst patterns, enabling adversaries to infer users’ browsing activities and posing persisten...
With the explosive growth of the Internet of Things (IoT) and cloud-computing traffic, Intrusion Detection Systems (IDSs) have become a cornerstone of network security. However, modern traffic data often exhibits extreme class imbalance and long-tail...
Efficiently mapping hourly air quality at a fine scale (25 m) remains a computational challenge. This difficulty is heightened when aiming to accurately capture industrial plumes and time-varying traffic emissions. This paper presents a method for ge...
Encrypted traffic classification is a crucial part of privacy-preserving research. With the great success of artificial intelligence technology in fields such as image recognition and natural language processing, how to classify encrypted traffic bas...
Urban traffic anomaly detection is essential for intelligent transportation systems, particularly in smart city environments where fast identification of abnormal events can improve road safety and traffic management. This work proposes a novel ULSTM...
The imbalance between normal and attack samples in the industrial control systems (ICSs) network environment leads to the low recognition rate of the intrusion detection model for a few abnormal samples when classifying. Since traditional machine lea...
Increasing heavy metal pollution in the environment and the fact that pine needles are good bio-monitors for air pollutants was the reason to investigate their accumulation in pine needles in Vienna (Austria). Pinus nigra is widespread over the city,...
29 January 2019
Air pollution is a major environmental problem in the Kathmandu Valley. Specifically, roadside and traffic-related air pollution exposure levels were found at very high levels exceeding Nepal air quality standards for daily PM2.5. In an exposure stud...
Haul traffic on earthworks runways during construction works is an important factor of dust emission. Compacted soils surface become progressively degraded as the number of wheels passing increases. Fine particles are then segregated from the soil su...
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