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In every day, there is a great growth of the Internet and smart devices connected to the network. On the other hand, there is an increasing in number of malwares that attacks networks, devices, systems and apps. One of t...

Insider threats pose a significant and growing risk to organizational cybersecurity, with recent studies indicating a 47% increase in insider incidents from 2018 to 2022. This paper presents a comparative analysis of uns...

Abstract BackgroundDigital behaviors such as sleep, social interactions, and productivity reflect how individuals structure their daily lives. Among university students, online activity patterns mirror academ...

"Performance indicators of road networks are a long-lasting topic of research. Existing schemes assess network properties such as the average speed on road segments and the queuing time at intersections. The increasing a...

The fast evolution of Botnet malware made it extremely difficult to detect. Despite it can be just considered as a tool, nowadays it has become one of the most dangerous threats for system administrators. Botnets are us...

Materie / parole chiave: NEWELL, G. F; THE MIT PRESS; 388 N545t

Model-based reinforcement learning (RL) is anticipated to exhibit higher sample efficiency than model-free RL by utilizing a virtual environment model. However, obtaining sufficiently accurate representations of environm...

In computer network, communication from one computer to another computer can be intercepted, the way to intercept communication between network devices is with Address Resolution Protocol Poisoning attack. This attack ca...

An effective method of traffic state classification is crucial for managing urban traffic congestion. Existing methods usually assume a given number of state categories, which is not flexible if real applications are req...

Abstract Autonomous driving systems critically rely on the precise detection of distant, small traffic signs to ensure safe and efficient navigation. Nonetheless, existing detection algorithms are confronted with several...

Macroscopic Fundamental Diagrams (MFDs) are valuable for designing and evaluating network-wide traffic management schemes. Since obtaining empirical MFDs can be expensive, analytical methodologies are crucial to estimate...

Network-wide traffic flow, which captures dynamic traffic volume on each link of a general network, is fundamental to smart mobility applications. However, the observed traffic flow from sensors is usually limited across...

Abstract The emergence of connected and automated vehicles (CAV) indicates improved traffic mobility in future traffic transportation systems. This study addresses the research gap in macroscopic traffic modeling of mixe...

This paper proposes three novel integer linear programming (ILP) formulations, where the first model deals with the Grooming, Routing, Wavelength Assignment, and Carrier Ethernet Interface Allocation Problem (GRWA-I); th...

Abstract The increase in vehicle ownership and urban population puts a strain on roads and increases traffic congestion within developed and developing nations. Congestion affects an individual’s time and increases an ...

Accurate traffic flow prediction is of great significance for urban planning and traffic management. Among existing methods, researchers have shown remarkable progress by utilizing spatiotemporal networks. Unfortunately,...

Abstract The rapid adoption of encrypted communication protocols has raised privacy levels but has also dealt a significant blow to traditional intrusion detection systems that rely on payload inspection for anomaly dete...

The data-driven Intelligent Transportation System (ITS) provides great support to travel decisions and system management but inevitably encounters the issue of data missing in monitoring systems. Hence, network-wide traf...

Traffic congestion degrades urban mobility and economic productivity, yet existing sensor-based monitoring systems detect only where congestion occurs without distinguishing its underlying infrastructure causes. This pap...

Abstract Traffic flow prediction is a fundamental building block for Intelligent Transportation Systems (ITS), enabling proactive congestion mitigation, adaptive traffic signal control, and reliable route guidance. Howev...

Urban air mobility (UAM) represents a transformative approach to alleviating ground-level congestion by transitioning from two-dimension (2D) to three-dimension (3D) transportation systems. Envisioned as a safe, sustaina...

Abstract Modern broadband access networks increasingly carry heterogeneous, delay-sensitive traffic generated by cloud-assisted applications, real-time communication services, and short-form multimedia exchanges. These w...

Efficiently solving the user equilibrium traffic assignment problem with elastic demand (UE-TAPED) for transportation networks is a critical problem for transportation studies. Most existing UE-TAPED algorithms are desig...

The dynamic range limitation is intrinsic to conventional RGB cameras, which reduces global contrast and causes the loss of high-frequency details such as textures and edges in complex, dynamic traffic environments (e.g....