888 research outputs found

    SUTMS - Unified Threat Management Framework for Home Networks

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    Home networks were initially designed for web browsing and non-business critical applications. As infrastructure improved, internet broadband costs decreased, and home internet usage transferred to e-commerce and business-critical applications. Today’s home computers host personnel identifiable information and financial data and act as a bridge to corporate networks via remote access technologies like VPN. The expansion of remote work and the transition to cloud computing have broadened the attack surface for potential threats. Home networks have become the extension of critical networks and services, hackers can get access to corporate data by compromising devices attacked to broad- band routers. All these challenges depict the importance of home-based Unified Threat Management (UTM) systems. There is a need of unified threat management framework that is developed specifically for home and small networks to address emerging security challenges. In this research, the proposed Smart Unified Threat Management (SUTMS) framework serves as a comprehensive solution for implementing home network security, incorporating firewall, anti-bot, intrusion detection, and anomaly detection engines into a unified system. SUTMS is able to provide 99.99% accuracy with 56.83% memory improvements. IPS stands out as the most resource-intensive UTM service, SUTMS successfully reduces the performance overhead of IDS by integrating it with the flow detection mod- ule. The artifact employs flow analysis to identify network anomalies and categorizes encrypted traffic according to its abnormalities. SUTMS can be scaled by introducing optional functions, i.e., routing and smart logging (utilizing Apriori algorithms). The research also tackles one of the limitations identified by SUTMS through the introduction of a second artifact called Secure Centralized Management System (SCMS). SCMS is a lightweight asset management platform with built-in security intelligence that can seamlessly integrate with a cloud for real-time updates

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    GPS Anomaly Detection And Machine Learning Models For Precise Unmanned Aerial Systems

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    The rapid development and deployment of 5G/6G networks have brought numerous benefits such as faster speeds, enhanced capacity, improved reliability, lower latency, greater network efficiency, and enablement of new applications. Emerging applications of 5G impacting billions of devices and embedded electronics also pose cyber security vulnerabilities. This thesis focuses on the development of Global Positioning Systems (GPS) Based Anomaly Detection and corresponding algorithms for Unmanned Aerial Systems (UAS). Chapter 1 provides an overview of the thesis background and its objectives. Chapter 2 presents an overview of the 5G architectures, their advantages, and potential cyber threat types. Chapter 3 addresses the issue of GPS dropouts by taking the use case of the Dallas-Fort Worth (DFW) airport. By analyzing data from surveillance drones in the (DFW) area, its message frequency, and statistics on time differences between GPS messages were examined. Chapter 4 focuses on modeling and detecting false data injection (FDI) on GPS. Specifically, three scenarios, including Gaussian noise injection, data duplication, data manipulation are modeled. Further, multiple detection schemes that are Clustering-based and reinforcement learning techniques are deployed and detection accuracy were investigated. Chapter 5 shows the results of Chapters 3 and 4. Overall, this research provides a categorization and possible outlier detection to minimize the GPS interference for UAS enhancing the security and reliability of UAS operations

    In-band-full-duplex integrated access and backhaul enabled next generation wireless networks

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    In sixth generation (6G) wireless networks, the severe traffic congestion in the microwave frequencies motivates the exploration of the large available bandwidth in the millimetre-wave (mmWave) frequencies to achieve higher network capacity and data rate. Since large-scale antenna arrays and dense base station deployment are required, the hybrid beamforming architecture and the recently proposed integrated access and backhaul (IAB) networks become potential candidates for providing cost and hardware-friendly techniques for 6G wireless networks. In addition, in-band-full-duplex (IBFD) has been recently paid much more research attention since it can make the transmission and reception occur in the same time and frequency band, which nearly doubles the communication spectral efficiency (SE) compared with state-of-the-art half-duplex (HD) systems. Since 6G will explore sensing as its new capability, future wireless networks can go far beyond communications. Motivated by this, the development of integrated sensing and communications (ISAC) systems, where radar and communication systems share the same spectrum resources and hardware, has become one of the major goals in 6G. This PhD thesis focuses on the design and analysis of IBFD-IAB wireless networks in the frequency range 2 (FR2) band (≥ 24.250 GHz) at mmWave frequencies for the potential use in 6G. Firstly, we develop a novel design for the single-cell FR2-IBFD-IAB networks with subarray-based hybrid beamforming, which can enhance the SE and coverage while reducing the latency. The radio frequency (RF) beamformers are obtained via RF codebooks given by a modified matrix-wise Linde-Buzo-Gray (LBG) algorithm. The self-interference (SI) is cancelled in three stages, where the first stage of antenna isolation is assumed to be successfully deployed. The second stage consists of the optical domain-based RF cancellation, where cancellers are connected with the RF chain pairs. The third stage is comprised of the digital cancellation via successive interference cancellation followed by minimum mean-squared error (MSE) baseband receiver. Multiuser interference in the access link is cancelled by zero-forcing at the IAB-node transmitter. The proposed codebook algorithm avoids undesirable low-rank behaviour, while the proposed staged-SI cancellation (SIC) shows satisfactory cancellation performance in the wideband IBFD scenario. However, the system performance can be affected by the hardware impairments (HWI) and RF effective channel estimation errors. Secondly, we study an FR2-IBFD-ISAC-IAB network for vehicle-to-everything communications, where the IAB-node acts as a roadside unit performing sensing and communication simultaneously (i.e., at the same time and frequency band). The SI due to the IBFD operation will be cancelled in the propagation, analogue, and digital domains; only the residual SI (RSI) is reserved for performance analysis. Considering the subarray-based hybrid beamforming structure, including HWI and RF effective SI channel estimation error, the unscented Kalman filter is used for tracking multiple vehicles in the studied scenario. The proposed system shows an enhanced SE compared with the HD system, and the tracking MSEs averaged across all vehicles of each state parameter are close to their posterior Cramér-Rao lower bounds. Thirdly, we analyse the performance of the multi-cell wideband single-hop backhaul FR2-IBFD-IAB networks by using stochastic geometry analysis. We model the wired-connected next generation NodeBs (gNBs) as the Matérn hard-core point process (MHCPP) to meet the real-world deployment requirement and reduce the cost caused by wired connection in the network. We first derive association probabilities that reflect how likely the typical user-equipment is served by a gNB or an IAB-node based on the maximum long-term averaged biased-received-desired-signal power criteria. Further, by leveraging the composite Gamma-Lognormal distribution, we derive results for the signal to interference plus noise ratio coverage, capacity with outage, and ergodic capacity of the network. In order to assess the impact of noise, we consider the sidelobe gain on inter-cell interference links and the analogue to digital converter quantization noise. Compared with the HD transmission, the designated system shows an enhanced capacity when the SIC operates successfully. We also study how the power bias and density ratio of the IAB-node to gNB, and the hard-core distance can affect system performance. Overall, this thesis aims to contribute to the research efforts of shaping the 6G wireless networks by designing and analysing the FR2-IBFD-IAB inspired networks in the FR2 band at mmWave frequencies that will be potentially used in 6G for both communication only and ISAC scenarios

    Environmentally-Aware and Energy-Efficient Multi-Drone Coordination and Networking for Disaster Response

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    In a Disaster Response Management (DRM) Scenario, Communication and Coordination Are Limited, and Absence of Related Infrastructure Hinders Situational Awareness. Unmanned Aerial Vehicles (UAVs) or Drones Provide New Capabilities for DRM to Address These Barriers. However, There is a Dearth of Works that Address Multiple Heterogeneous Drones Collaboratively Working Together to Form a Flying Ad-Hoc Network (FANET) with Air-To-Air and Air-To-Ground Links that Are Impacted By: (I) Environmental Obstacles, (Ii) Wind, and (Iii) Limited Battery Capacities. in This Paper, We Present a Novel Environmentally-Aware and Energy-Efficient Multi-Drone Coordination and Networking Scheme that Features a Reinforcement Learning (RL) based Location Prediction Algorithm Coupled with a Packet Forwarding Algorithm for Drone-To-Ground Network Establishment. We Specifically Present Two Novel Drone Location-Based Solutions (I.e., Heuristic Greedy, and Learning-Based) in Our Packet Forwarding Approach to Support Application Requirements. These Requirements Involve Improving Connectivity (I.e., Optimize Packet Delivery Ratio and End-To-End Delay) Despite Environmental Obstacles, and Improving Efficiency (I.e., by Lower Energy Use and Time Consumption) Despite Energy Constraints. We Evaluate Our Scheme with State-Of-The-Art Networking Algorithms in a Trace-Based DRM FANET Simulation Testbed Featuring Rural and Metropolitan Areas. Results Show that Our Strategy overcomes Obstacles and Can Achieve 81-To-90% of Network Connectivity Performance Observed under No Obstacle Conditions. in the Presence of Obstacles, Our Scheme Improves the Network Connectivity Performance by 14-To-38% While Also Providing 23-To-54% of Energy Savings in Rural Areas; the Same in Metropolitan Areas Achieved an Average of 25% Gain When Compared with Baseline Obstacle Awareness Approaches with 15-To-76% of Energy Savings

    Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services

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    This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book

    Applications of graph theory to wireless networks and opinion analysis

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    La teoría de grafos es una rama importante dentro de la matemática discreta. Su uso ha aumentado recientemente dada la conveniencia de los grafos para estructurar datos, para analizarlos y para generarlos a través de modelos. El objetivo de esta tesis es aplicar teoría de grafos a la optimización de redes inalámbricas y al análisis de opinión. El primer conjunto de contribuciones de esta tesis versa sobre la aplicación de teoría de grafos a redes inalámbricas. El rendimiento de estas redes depende de la correcta distribución de canales de frecuencia en un espacio compartido. Para optimizar estas redes se proponen diferentes técnicas, desde la aplicación de heurísticas como simulated annealing a la negociación automática. Cualquiera de estas técnicas requiere un modelo teórico de la red inalámbrica en cuestión. Nuestro modelo de redes Wi-Fi utiliza grafos geométricos para este propósito. Los vértices representan los dispositivos de la red, sean clientes o puntos de acceso, mientras que las aristas representan las señales entre dichos dispositivos. Estos grafos son de tipo geométrico, por lo que los vértices tienen posición en el espacio, y las aristas tienen longitud. Con esta estructura y la aplicación de un modelo de propagación y de uso, podemos simular redes inalámbricas y contribuir a su optimización. Usando dicho modelo basado en grafos, hemos estudiado el efecto de la interferencia cocanal en redes Wi-Fi 4 y mostramos una mejora de rendimiento asociada a la técnica de channel bonding cuando se usa en regiones donde hay por lo menos 13 canales disponibles. Por otra parte, en esta tesis doctoral hemos aplicado teoría de grafos al análisis de opinión dentro de la línea de investigación de SensoGraph, un método con el que se realiza un análisis de opinión sobre un conjunto de elementos usando grafos de proximidad, lo que permite manejar grandes conjuntos de datos. Además, hemos desarrollado un método de análisis de opinión que emplea la asignación manual de aristas y distancias en un grafo para estudiar la similaridad entre las muestras dos a dos. Adicionalmente, se han explorado otros temas sin relación con los grafos, pero que entran dentro de la aplicación de las matemáticas a un problema de la ingeniería telemática. Se ha desarrollado un sistema de votación electrónica basado en mixnets, secreto compartido de Shamir y cuerpos finitos. Dicha propuesta ofrece un sistema de verificación numérico novedoso a la vez que mantiene las propiedades esenciales de los sistemas de votación

    Direct communication radio Iinterface for new radio multicasting and cooperative positioning

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    Cotutela: Universidad de defensa UNIVERSITA’ MEDITERRANEA DI REGGIO CALABRIARecently, the popularity of Millimeter Wave (mmWave) wireless networks has increased due to their capability to cope with the escalation of mobile data demands caused by the unprecedented proliferation of smart devices in the fifth-generation (5G). Extremely high frequency or mmWave band is a fundamental pillar in the provision of the expected gigabit data rates. Hence, according to both academic and industrial communities, mmWave technology, e.g., 5G New Radio (NR) and WiGig (60 GHz), is considered as one of the main components of 5G and beyond networks. Particularly, the 3rd Generation Partnership Project (3GPP) provides for the use of licensed mmWave sub-bands for the 5G mmWave cellular networks, whereas IEEE actively explores the unlicensed band at 60 GHz for the next-generation wireless local area networks. In this regard, mmWave has been envisaged as a new technology layout for real-time heavy-traffic and wearable applications. This very work is devoted to solving the problem of mmWave band communication system while enhancing its advantages through utilizing the direct communication radio interface for NR multicasting, cooperative positioning, and mission-critical applications. The main contributions presented in this work include: (i) a set of mathematical frameworks and simulation tools to characterize multicast traffic delivery in mmWave directional systems; (ii) sidelink relaying concept exploitation to deal with the channel condition deterioration of dynamic multicast systems and to ensure mission-critical and ultra-reliable low-latency communications; (iii) cooperative positioning techniques analysis for enhancing cellular positioning accuracy for 5G+ emerging applications that require not only improved communication characteristics but also precise localization. Our study indicates the need for additional mechanisms/research that can be utilized: (i) to further improve multicasting performance in 5G/6G systems; (ii) to investigate sideline aspects, including, but not limited to, standardization perspective and the next relay selection strategies; and (iii) to design cooperative positioning systems based on Device-to-Device (D2D) technology
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