1,720,953 research outputs found
Detecting and mitigating the distributed denial of service attacks in software defined networks using machine learning approach - the integrated random forest and K-nearest neighbours classifiers
Get PDFThesis (M.Sc.(Computer Science) -- University of Limpopo, 2023Distributed Denial of Service (DDoS) attacks present substantial risks to network availability and stability, especially within the realm of Software Defined Networks (SDNs). Inventive and efficient detection and mitigation methods become imperative to counter the continuously evolving nature of these attacks.
SDN is characterized by its dynamic and programmable nature and is susceptible to DDoS attacks that can disrupt network operations. Traditional methods for detecting and mitigating DDoS attacks in SDNs may not be sufficient due to the evolving nature of these attacks. The research aims to develop a more effective and adaptive solution by using the Random Forest (RF) and k-Nearest Neighbours (KNN) machine learning algorithms. This approach seeks to enhance the accuracy, speed, and resilience of DDoS detection and mitigation in SDN networks.
The research aims to address the pressing need for robust DDoS detection and mitigation mechanisms in SDNs by harnessing the power of machine learning, through the integration of RF and KNN and improving the KNN model. This approach is motivated by the evolving threat landscape, the unique challenges posed by SDN environments, and the potential for advanced machine learning techniques to enhance network security.
Furthermore, the research objective is to enhance the K-Nearest Neighbors (KNN) classification algorithm. By looking deep into KNN and addressing its limitations, this study seeks to refine and optimize the algorithm's performance for various real-world applications. Through a systematic exploration of parameter tuning, feature engineering, and innovative techniques, this research aims to provide a more accurate and efficient KNN classifier.
This study investigates the utilization of a machine learning approach, specifically Random Forest and K-Nearest Neighbours classifiers, to identify and counteract Distributed Denial of Service (DDoS) attacks in Software Defined Networks (SDNs). The research commences by exploring the fundamental concepts of SDNs and DDoS attacks, highlighting their interplay and the unique challenges they pose to network availability and stability. The methodology for the study typically involves steps such as Data Collection (gathering network traffic data from SDN, including both normal and potentially malicious traffic.), Data Preprocessing (Clean and preprocess the collected data to remove noise, handle missing values, and normalize features), Feature Engineering: Identify relevant features or attributes in the network traffic data that can help distinguish between normal and DDoS attack traffic. By following the methodology presented in this study, we can systematically investigate the feasibility and efficacy of the proposed approach for detecting and mitigating DDoS attacks in SDN.
A comprehensive review of existing literature is conducted to understand the state-of- the-art techniques employed for DDoS detection and mitigation, with an emphasis on machine learning approaches. Expanding on the current understanding of mitigation against attacks, this thesis suggests employing Random Forest and K-Nearest Neighbours classifiers to improve the precision and effectiveness of DDoS detection in SDN environments. The proposed framework utilizes the ensemble learning abilities of Random Forest to address the challenges posed by the complex and diverse network traffic features, while the K-Nearest Neighbours algorithm offers the necessary flexibility and prompt decision-making for timely mitigation.
To evaluate the proposed model, extensive experiments are conducted using a realistic SDN simulator and diverse DDoS attack scenarios. Multiple performance metrics, including accuracy of detection, rate of false positives, and response time, are assessed and compared to alternative methods. The results demonstrate the superiority of the Random Forest and K-Nearest Neighbours classifiers in detecting and mitigating DDoS attacks effectively, efficiently, and with minimal impact on legitimate traffic.
In conclusion, this study shows that the improved KNN algorithm with a n_neighbours value of 2 has a higher accuracy rate compared to the Decision Tree classifier.
Furthermore, this research explores the challenges and limitations associated with the proposed model and provides insights for further improvements. This dissertation makes a valuable contribution to the domain of network security by introducing a novel methodology that employs machine learning techniques to identify and counteract DDoS attacks in SDNs. The model presented not only enhances the precision of attack detection but also diminishes response time, empowering network administrators to
safeguard their SDN infrastructure against intricate and evolving DDoS attacks effectively
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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