Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Methodologies And Techniques For Analysis Of Network Flow Data
Download Methodologies And Techniques For Analysis Of Network Flow Data full books in PDF, epub, and Kindle. Read online Methodologies And Techniques For Analysis Of Network Flow Data ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Methodologies and Techniques for Analysis of Network Flow Data by : M. Grigoriev
Download or read book Methodologies and Techniques for Analysis of Network Flow Data written by M. Grigoriev and published by . This book was released on 2004 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network flow data gathered at the border routers and core switches is used at Fermilab for statistical analysis of traffic patterns, passive network monitoring, and estimation of network performance characteristics. Flow data is also a critical tool in the investigation of computer security incidents. Development and enhancement of flow based tools is an on-going effort. This paper describes the most recent developments in flow analysis at Fermilab.
Book Synopsis Statistical Analysis of Network Data by : Eric D. Kolaczyk
Download or read book Statistical Analysis of Network Data written by Eric D. Kolaczyk and published by Springer Science & Business Media. This book was released on 2009-04-20 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.
Book Synopsis Fundamentals of Brain Network Analysis by : Alex Fornito
Download or read book Fundamentals of Brain Network Analysis written by Alex Fornito and published by Academic Press. This book was released on 2016-03-04 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. - Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology - Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems - Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience - Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain
Book Synopsis The SAGE Handbook of Social Network Analysis by : John Scott
Download or read book The SAGE Handbook of Social Network Analysis written by John Scott and published by SAGE Publications. This book was released on 2011-05-25 with total page 641 pages. Available in PDF, EPUB and Kindle. Book excerpt: This sparkling Handbook offers an unrivalled resource for those engaged in the cutting edge field of social network analysis. Systematically, it introduces readers to the key concepts, substantive topics, central methods and prime debates. Among the specific areas covered are: Network theory Interdisciplinary applications Online networks Corporate networks Lobbying networks Deviant networks Measuring devices Key Methodologies Software applications. The result is a peerless resource for teachers and students which offers a critical survey of the origins, basic issues and major debates. The Handbook provides a one-stop guide that will be used by readers for decades to come.
Book Synopsis Statistical Methods for QTL Mapping by : Zehua Chen
Download or read book Statistical Methods for QTL Mapping written by Zehua Chen and published by CRC Press. This book was released on 2013-11-01 with total page 944 pages. Available in PDF, EPUB and Kindle. Book excerpt: While numerous advanced statistical approaches have recently been developed for quantitative trait loci (QTL) mapping, the methods are scattered throughout the literature. Statistical Methods for QTL Mapping brings together many recent statistical techniques that address the data complexity of QTL mapping. After introducing basic genetics topics and statistical principles, the author discusses the principles of quantitative genetics, general statistical issues of QTL mapping, commonly used one-dimensional QTL mapping approaches, and multiple interval mapping methods. He then explains how to use a feature selection approach to tackle a QTL mapping problem with dense markers. The book also provides comprehensive coverage of Bayesian models and MCMC algorithms and describes methods for multi-trait QTL mapping and eQTL mapping, including meta-trait methods and multivariate sequential procedures. This book emphasizes the modern statistical methodology for QTL mapping as well as the statistical issues that arise during this process. It gives the necessary biological background for statisticians without training in genetics and, likewise, covers statistical thinking and principles for geneticists. Written primarily for geneticists and statisticians specializing in QTL mapping, the book can also be used as a supplement in graduate courses or for self-study by PhD students working on QTL mapping projects.
Author :Federico Montesino Pouzols Publisher :Springer Science & Business Media ISBN 13 :3642180833 Total Pages :322 pages Book Rating :4.6/5 (421 download)
Book Synopsis Mining and Control of Network Traffic by Computational Intelligence by : Federico Montesino Pouzols
Download or read book Mining and Control of Network Traffic by Computational Intelligence written by Federico Montesino Pouzols and published by Springer Science & Business Media. This book was released on 2011-02-10 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: As other complex systems in social and natural sciences as well as in engineering, the Internet is hard to understand from a technical point of view. Packet switched networks defy analytical modeling. The Internet is an outstanding and challenging case because of its fast development, unparalleled heterogeneity and the inherent lack of measurement and monitoring mechanisms in its core conception. This monograph deals with applications of computational intelligence methods, with an emphasis on fuzzy techniques, to a number of current issues in measurement, analysis and control of traffic in the Internet. First, the core building blocks of Internet Science and other related networking aspects are introduced. Then, data mining and control problems are addressed. In the first class two issues are considered: predictive modeling of traffic load as well as summarization of traffic flow measurements. The second class, control, includes active queue management schemes for Internet routers as well as window based end-to-end rate and congestion control. The practical hardware implementation of some of the fuzzy inference systems proposed here is also addressed. While some theoretical developments are described, we favor extensive evaluation of models using real-world data by simulation and experiments.
Book Synopsis Encrypted Network Traffic Analysis by : Aswani Kumar Cherukuri
Download or read book Encrypted Network Traffic Analysis written by Aswani Kumar Cherukuri and published by Springer Nature. This book was released on with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Network Analysis, Architecture and Design by : James D. McCabe
Download or read book Network Analysis, Architecture and Design written by James D. McCabe and published by Morgan Kaufmann Publishers. This book was released on 2003 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by a seasoned network architect who has led numerous design projects in government, commercial, and academic spaces, this volume is significantly updated to include an entirely new section on architecture as well as containing completely revised material on analysis and design.
Book Synopsis Proceedings of the International Conference on IT Convergence and Security 2011 by : Kuinam J. Kim
Download or read book Proceedings of the International Conference on IT Convergence and Security 2011 written by Kuinam J. Kim and published by Springer Science & Business Media. This book was released on 2011-12-07 with total page 605 pages. Available in PDF, EPUB and Kindle. Book excerpt: As we entered the 21st century, the rapid growth of information technology has changed our lives more conveniently than we have ever speculated. Recently in all fields of the industry, heterogeneous technologies have converged with information technology resulting in a new paradigm, information technology convergence. In the process of information technology convergence, the latest issues in the structure of data, system, network, and infrastructure have become the most challenging task. Proceedings of the International Conference on IT Convergence and Security 2011 approaches the subject matter with problems in technical convergence and convergences of security technology by looking at new issues that arise from techniques converging. The general scope is convergence security and the latest information technology with the following most important features and benefits: 1. Introduction of the most recent information technology and its related ideas 2. Applications and problems related to technology convergence, and its case studies 3. Introduction of converging existing security techniques through convergence security Overall, after reading Proceedings of the International Conference on IT Convergence and Security 2011, readers will understand the most state of the art information strategies and technologies of convergence security.
Book Synopsis Learning Analytics Methods and Tutorials by : Mohammed Saqr
Download or read book Learning Analytics Methods and Tutorials written by Mohammed Saqr and published by Springer Nature. This book was released on with total page 748 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Technologies and Innovation by : Rafael Valencia-García
Download or read book Technologies and Innovation written by Rafael Valencia-García and published by Springer Nature. This book was released on with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis New Frontiers in Artificial Intelligence by : Takashi Washio
Download or read book New Frontiers in Artificial Intelligence written by Takashi Washio and published by Springer Science & Business Media. This book was released on 2007-01-18 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed joint post-proceedings of three international workshops organized by the Japanese Society for Artificial Intelligence, held in Tokyo, Japan in June 2006 during the 20th Annual Conference JSAI 2006. The volume starts with eight award winning papers of the JSAI 2006 main conference that are presented along with the 21 revised full workshop papers, carefully reviewed and selected for inclusion in the volume.
Book Synopsis Network Traffic Anomaly Detection and Prevention by : Monowar H. Bhuyan
Download or read book Network Traffic Anomaly Detection and Prevention written by Monowar H. Bhuyan and published by Springer. This book was released on 2017-09-03 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This indispensable text/reference presents a comprehensive overview on the detection and prevention of anomalies in computer network traffic, from coverage of the fundamental theoretical concepts to in-depth analysis of systems and methods. Readers will benefit from invaluable practical guidance on how to design an intrusion detection technique and incorporate it into a system, as well as on how to analyze and correlate alerts without prior information. Topics and features: introduces the essentials of traffic management in high speed networks, detailing types of anomalies, network vulnerabilities, and a taxonomy of network attacks; describes a systematic approach to generating large network intrusion datasets, and reviews existing synthetic, benchmark, and real-life datasets; provides a detailed study of network anomaly detection techniques and systems under six different categories: statistical, classification, knowledge-base, cluster and outlier detection, soft computing, and combination learners; examines alert management and anomaly prevention techniques, including alert preprocessing, alert correlation, and alert post-processing; presents a hands-on approach to developing network traffic monitoring and analysis tools, together with a survey of existing tools; discusses various evaluation criteria and metrics, covering issues of accuracy, performance, completeness, timeliness, reliability, and quality; reviews open issues and challenges in network traffic anomaly detection and prevention. This informative work is ideal for graduate and advanced undergraduate students interested in network security and privacy, intrusion detection systems, and data mining in security. Researchers and practitioners specializing in network security will also find the book to be a useful reference.
Book Synopsis Data Flow Analysis by : Uday Khedker
Download or read book Data Flow Analysis written by Uday Khedker and published by CRC Press. This book was released on 2017-12-19 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data flow analysis is used to discover information for a wide variety of useful applications, ranging from compiler optimizations to software engineering and verification. Modern compilers apply it to produce performance-maximizing code, and software engineers use it to re-engineer or reverse engineer programs and verify the integrity of their programs. Supplementary Online Materials to Strengthen Understanding Unlike most comparable books, many of which are limited to bit vector frameworks and classical constant propagation, Data Flow Analysis: Theory and Practice offers comprehensive coverage of both classical and contemporary data flow analysis. It prepares foundations useful for both researchers and students in the field by standardizing and unifying various existing research, concepts, and notations. It also presents mathematical foundations of data flow analysis and includes study of data flow analysis implantation through use of the GNU Compiler Collection (GCC). Divided into three parts, this unique text combines discussions of inter- and intraprocedural analysis and then describes implementation of a generic data flow analyzer (gdfa) for bit vector frameworks in GCC. Through the inclusion of case studies and examples to reinforce material, this text equips readers with a combination of mutually supportive theory and practice, and they will be able to access the author’s accompanying Web page. Here they can experiment with the analyses described in the book, and can make use of updated features, including: Slides used in the authors’ courses The source of the generic data flow analyzer (gdfa) An errata that features errors as they are discovered Additional updated relevant material discovered in the course of research
Book Synopsis Modeling and Analysis of Computer Communications Networks by : Jeremiah F. Hayes
Download or read book Modeling and Analysis of Computer Communications Networks written by Jeremiah F. Hayes and published by Springer Science & Business Media. This book was released on 2013-03-08 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: In large measure the traditional concern of communications engineers has been the conveyance of voice signals. The most prominent example is the telephone network, in which the techniques used for transmission multiplex ing and switching have been designed for voice signals. However, one of the many effects of computers has been the growing volume of the sort of traffic that flows in networks composed of user terminals, processors, and peripherals. The characteristics of this data traffic and the associated perfor mance requirements are quite different from those of voice traffic. These differences, coupled with burgeoning digital technology, have engendered a whole new set of approaches to multiplexing and switching this traffic. The new techniques are the province of what has been loosely called computer communications networks. The subject of this book is the mathematical modeling and analysis of computer communications networks, that is to say, the multiplexing and switching techniques that have been developed for data traffic. The basis for many of the models that we shall consider is queueing theory, although a number of other disciplines are drawn on as well. The level at which this material is covered is that of a first-year graduate course. It is assumed that at the outset the student has had a good undergraduate course in probability and random processes of the sort that are more and more common among electrical engineering and computer science departments.
Book Synopsis Robust Network Compressive Sensing by : Guangtao Xue
Download or read book Robust Network Compressive Sensing written by Guangtao Xue and published by Springer Nature. This book was released on 2022-10-22 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book investigates compressive sensing techniques to provide a robust and general framework for network data analytics. The goal is to introduce a compressive sensing framework for missing data interpolation, anomaly detection, data segmentation and activity recognition, and to demonstrate its benefits. Chapter 1 introduces compressive sensing, including its definition, limitation, and how it supports different network analysis applications. Chapter 2 demonstrates the feasibility of compressive sensing in network analytics, the authors we apply it to detect anomalies in the customer care call dataset from a Tier 1 ISP in the United States. A regression-based model is applied to find the relationship between calls and events. The authors illustrate that compressive sensing is effective in identifying important factors and can leverage the low-rank structure and temporal stability to improve the detection accuracy. Chapter 3 discusses that there are several challenges in applying compressive sensing to real-world data. Understanding the reasons behind the challenges is important for designing methods and mitigating their impact. The authors analyze a wide range of real-world traces. The analysis demonstrates that there are different factors that contribute to the violation of the low-rank property in real data. In particular, the authors find that (1) noise, errors, and anomalies, and (2) asynchrony in the time and frequency domains lead to network-induced ambiguity and can easily cause low-rank matrices to become higher-ranked. To address the problem of noise, errors and anomalies in Chap. 4, the authors propose a robust compressive sensing technique. It explicitly accounts for anomalies by decomposing real-world data represented in matrix form into a low-rank matrix, a sparse anomaly matrix, an error term and a small noise matrix. Chapter 5 addresses the problem of lack of synchronization, and the authors propose a data-driven synchronization algorithm. It can eliminate misalignment while taking into account the heterogeneity of real-world data in both time and frequency domains. The data-driven synchronization can be applied to any compressive sensing technique and is general to any real-world data. The authors illustrates that the combination of the two techniques can reduce the ranks of real-world data, improve the effectiveness of compressive sensing and have a wide range of applications. The networks are constantly generating a wealth of rich and diverse information. This information creates exciting opportunities for network analysis and provides insight into the complex interactions between network entities. However, network analysis often faces the problems of (1) under-constrained, where there is too little data due to feasibility and cost issues in collecting data, or (2) over-constrained, where there is too much data, so the analysis becomes unscalable. Compressive sensing is an effective technique to solve both problems. It utilizes the underlying data structure for analysis. Specifically, to solve the under-constrained problem, compressive sensing technologies can be applied to reconstruct the missing elements or predict the future data. Also, to solve the over-constraint problem, compressive sensing technologies can be applied to identify significant elements To support compressive sensing in network data analysis, a robust and general framework is needed to support diverse applications. Yet this can be challenging for real-world data where noise, anomalies and lack of synchronization are common. First, the number of unknowns for network analysis can be much larger than the number of measurements. For example, traffic engineering requires knowing the complete traffic matrix between all source and destination pairs, in order to properly configure traffic and avoid congestion. However, measuring the flow between all source and destination pairs is very expensive or even infeasible. Reconstructing data from a small number of measurements is an underconstrained problem. In addition, real-world data is complex and heterogeneous, and often violate the low-level assumptions required by existing compressive sensing techniques. These violations significantly reduce the applicability and effectiveness of existing compressive sensing methods. Third, synchronization of network data reduces the data ranks and increases spatial locality. However, periodic time series exhibit not only misalignment but also different frequencies, which makes it difficult to synchronize data in the time and frequency domains. The primary audience for this book is data engineers, analysts and researchers, who need to deal with big data with missing anomalous and synchronization problems. Advanced level students focused on compressive sensing techniques will also benefit from this book as a reference.
Book Synopsis Network Flow Analysis by : Michael Lucas
Download or read book Network Flow Analysis written by Michael Lucas and published by No Starch Press. This book was released on 2010 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed and complete guide to exporting, collecting, analyzing, and understanding network flows to make managing networks easier. Network flow analysis is the art of studying the traffic on a computer network. Understanding the ways to export flow and collect and analyze data separates good network administrators from great ones. The detailed instructions in Network Flow Analysis teach the busy network administrator how to build every component of a flow-based network awareness system and how network analysis and auditing can help address problems and improve network reliability. Readers learn what flow is, how flows are used in network management, and how to use a flow analysis system. Real-world examples illustrate how to best apply the appropriate tools and how to analyze data to solve real problems. Lucas compares existing popular tools for network management, explaining why they don't address common real-world issues and demonstrates how, once a network administrator understands the underlying process and techniques of flow management, building a flow management system from freely-available components is not only possible but actually a better choice than much more expensive systems.
