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Full-Text Articles in Computer Engineering
Toward Building An Intelligent And Secure Network: An Internet Traffic Forecasting Perspective, Sajal Saha
Toward Building An Intelligent And Secure Network: An Internet Traffic Forecasting Perspective, Sajal Saha
Electronic Thesis and Dissertation Repository
Internet traffic forecast is a crucial component for the proactive management of self-organizing networks (SON) to ensure better Quality of Service (QoS) and Quality of Experience (QoE). Given the volatile and random nature of traffic data, this forecasting influences strategic development and investment decisions in the Internet Service Provider (ISP) industry. Modern machine learning algorithms have shown potential in dealing with complex Internet traffic prediction tasks, yet challenges persist. This thesis systematically explores these issues over five empirical studies conducted in the past three years, focusing on four key research questions: How do outlier data samples impact prediction accuracy for …
Classification Of Ddos Attack With Machine Learning Architectures And Exploratory Analysis, Amreen Anbar
Classification Of Ddos Attack With Machine Learning Architectures And Exploratory Analysis, Amreen Anbar
Electronic Thesis and Dissertation Repository
The ever-increasing frequency of occurrence and sophistication of DDoS attacks pose a serious threat to network security. Accurate classification of DDoS attacks with efficiency is crucial in order to develop effective defense mechanisms. In this thesis, we propose a novel approach for DDoS classification using the CatBoost algorithm, on CICDDoS2019, a benchmark dataset containing 12 variations of DDoS attacks and legitimate traffic using real-world traffic traces. With a developed ensemble feature selection method and feature engineering, our model proves to be a good fit for DDoS attack type prediction. Our experimental results demonstrate that our proposed approach achieves high classification …
Transforming Large-Scale Virtualized Networks: Advancements In Latency Reduction, Availability Enhancement, And Security Fortification, Ibrahim Tamim
Transforming Large-Scale Virtualized Networks: Advancements In Latency Reduction, Availability Enhancement, And Security Fortification, Ibrahim Tamim
Electronic Thesis and Dissertation Repository
In today’s digital age, the increasing demand for networks, driven by the proliferation of connected devices, data-intensive applications, and transformative technologies, necessitates robust and efficient network infrastructure. This thesis addresses the challenges posed by virtualization in 5G networking and focuses on enhancing next-generation Radio Access Networks (RANs), particularly Open-RAN (O-RAN). The objective is to transform virtualized networks into highly reliable, secure, and latency-aware systems. To achieve this, the thesis proposes novel strategies for virtual function placement, traffic steering, and virtual function security within O-RAN. These solutions utilize optimization techniques such as binary integer programming, mixed integer binary programming, column generation, …
Leveraging Machine Learning Techniques Towards Intelligent Networking Automation, Cesar A. Gomez
Leveraging Machine Learning Techniques Towards Intelligent Networking Automation, Cesar A. Gomez
Electronic Thesis and Dissertation Repository
In this thesis, we address some of the challenges that the Intelligent Networking Automation (INA) paradigm poses. Our goal is to design schemes leveraging Machine Learning (ML) techniques to cope with situations that involve hard decision-making actions. The proposed solutions are data-driven and consist of an agent that operates at network elements such as routers, switches, or network servers. The data are gathered from realistic scenarios, either actual network deployments or emulated environments. To evaluate the enhancements that the designed schemes provide, we compare our solutions to non-intelligent ones. Additionally, we assess the trade-off between the obtained improvements and the …
Real-Time Intrusion Detection Using Multidimensional Sequence-To-Sequence Machine Learning And Adaptive Stream Processing, Gobinath Loganathan
Real-Time Intrusion Detection Using Multidimensional Sequence-To-Sequence Machine Learning And Adaptive Stream Processing, Gobinath Loganathan
Electronic Thesis and Dissertation Repository
A network intrusion is any unauthorized activity on a computer network. There are host-based and network-based Intrusion Detection Systems (IDS's), of which there are each signature-based and anomaly-based detection methods. An anomalous network behavior can be defined as an intentional violation of the expected sequence of packets. In a real-time network-based IDS, incoming packets are treated as a stream of data. A stream processor takes any stream of data or events and extracts interesting patterns on the fly. This representation allows applying statistical anomaly detection using sequence prediction algorithms as well as using a stream processor to perform signature-based intrusion …