Download or read book Applied Network Security Monitoring written by Chris Sanders and published by Elsevier. This book was released on 2013-11-26 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Network Security Monitoring is the essential guide to becoming an NSM analyst from the ground up. This book takes a fundamental approach to NSM, complete with dozens of real-world examples that teach you the key concepts of NSM. Network security monitoring is based on the principle that prevention eventually fails. In the current threat landscape, no matter how much you try, motivated attackers will eventually find their way into your network. At that point, it is your ability to detect and respond to that intrusion that can be the difference between a small incident and a major disaster. The book follows the three stages of the NSM cycle: collection, detection, and analysis. As you progress through each section, you will have access to insights from seasoned NSM professionals while being introduced to relevant, practical scenarios complete with sample data. If you've never performed NSM analysis, Applied Network Security Monitoring will give you an adequate grasp on the core concepts needed to become an effective analyst. If you are already a practicing analyst, this book will allow you to grow your analytic technique to make you more effective at your job. - Discusses the proper methods for data collection, and teaches you how to become a skilled NSM analyst - Provides thorough hands-on coverage of Snort, Suricata, Bro-IDS, SiLK, and Argus - Loaded with practical examples containing real PCAP files you can replay, and uses Security Onion for all its lab examples - Companion website includes up-to-date blogs from the authors about the latest developments in NSM

Download or read book Practical Packet Analysis written by Chris Sanders and published by No Starch Press. This book was released on 2007 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides information on ways to use Wireshark to capture and analyze packets, covering such topics as building customized capture and display filters, graphing traffic patterns, and building statistics and reports.

Download or read book Network Analysis written by Ulrik Brandes and published by Springer. This book was released on 2005-02-02 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: ‘Network’ is a heavily overloaded term, so that ‘network analysis’ means different things to different people. Specific forms of network analysis are used in the study of diverse structures such as the Internet, interlocking directorates, transportation systems, epidemic spreading, metabolic pathways, the Web graph, electrical circuits, project plans, and so on. There is, however, a broad methodological foundation which is quickly becoming a prerequisite for researchers and practitioners working with network models. From a computer science perspective, network analysis is applied graph theory. Unlike standard graph theory books, the content of this book is organized according to methods for specific levels of analysis (element, group, network) rather than abstract concepts like paths, matchings, or spanning subgraphs. Its topics therefore range from vertex centrality to graph clustering and the evolution of scale-free networks. In 15 coherent chapters, this monograph-like tutorial book introduces and surveys the concepts and methods that drive network analysis, and is thus the first book to do so from a methodological perspective independent of specific application areas.

Download or read book Applied Social Network Analysis with R written by Mehmet Gençer and published by . This book was released on 2019-11 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book explores the structure of socio-economic relations, in particular, relations in business life"--

Download or read book Social Network Analysis with Applications written by Ian McCulloh and published by John Wiley & Sons. This book was released on 2013-07-01 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to social network analysis that hones in on basic centrality measures, social links, subgroup analysis, data sources, and more Written by military, industry, and business professionals, this book introduces readers to social network analysis, the new and emerging topic that has recently become of significant use for industry, management, law enforcement, and military practitioners for identifying both vulnerabilities and opportunities in collaborative networked organizations. Focusing on models and methods for the analysis of organizational risk, Social Network Analysis with Applications provides easily accessible, yet comprehensive coverage of network basics, centrality measures, social link theory, subgroup analysis, relational algebra, data sources, and more. Examples of mathematical calculations and formulas for social network measures are also included. Along with practice problems and exercises, this easily accessible book covers: The basic concepts of networks, nodes, links, adjacency matrices, and graphs Mathematical calculations and exercises for centrality, the basic measures of degree, betweenness, closeness, and eigenvector centralities Graph-level measures, with a special focus on both the visual and numerical analysis of networks Matrix algebra, outlining basic concepts such as matrix addition, subtraction, multiplication, and transpose and inverse calculations in linear algebra that are useful for developing networks from relational data Meta-networks and relational algebra, social links, diffusion through networks, subgroup analysis, and more An excellent resource for practitioners in industry, management, law enforcement, and military intelligence who wish to learn and apply social network analysis to their respective fields, Social Network Analysis with Applications is also an ideal text for upper-level undergraduate and graduate level courses and workshops on the subject.

Download or read book Network Analysis and Synthesis written by Brian D. O. Anderson and published by Courier Corporation. This book was released on 2013-01-30 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive look at linear network analysis and synthesis explores state-space synthesis as well as analysis, employing modern systems theory to unite classical concepts of network theory. 1973 edition.

Download or read book Inferential Network Analysis written by Skyler J. Cranmer and published by Cambridge University Press. This book was released on 2020-11-19 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pioneering introduction of unprecedented breadth and scope to inferential and statistical methods for network analysis.

Download or read book Probabilistic Foundations of Statistical Network Analysis written by Harry Crane and published by CRC Press. This book was released on 2018-04-17 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis. Its lucid exposition provides necessary background for understanding the essential ideas behind exchangeable and dynamic network models, network sampling, and network statistics such as sparsity and power law, all of which play a central role in contemporary data science and machine learning applications. The book rewards readers with a clear and intuitive understanding of the subtle interplay between basic principles of statistical inference, empirical properties of network data, and technical concepts from probability theory. Its mathematically rigorous, yet non-technical, exposition makes the book accessible to professional data scientists, statisticians, and computer scientists as well as practitioners and researchers in substantive fields. Newcomers and non-quantitative researchers will find its conceptual approach invaluable for developing intuition about technical ideas from statistics and probability, while experts and graduate students will find the book a handy reference for a wide range of new topics, including edge exchangeability, relative exchangeability, graphon and graphex models, and graph-valued Levy process and rewiring models for dynamic networks. The author’s incisive commentary supplements these core concepts, challenging the reader to push beyond the current limitations of this emerging discipline. With an approachable exposition and more than 50 open research problems and exercises with solutions, this book is ideal for advanced undergraduate and graduate students interested in modern network analysis, data science, machine learning, and statistics. Harry Crane is Associate Professor and Co-Director of the Graduate Program in Statistics and Biostatistics and an Associate Member of the Graduate Faculty in Philosophy at Rutgers University. Professor Crane’s research interests cover a range of mathematical and applied topics in network science, probability theory, statistical inference, and mathematical logic. In addition to his technical work on edge and relational exchangeability, relative exchangeability, and graph-valued Markov processes, Prof. Crane’s methods have been applied to domain-specific cybersecurity and counterterrorism problems at the Foreign Policy Research Institute and RAND’s Project AIR FORCE.

Download or read book Applied Network Analysis written by Ronald S. Burt and published by SAGE Publications, Incorporated. This book was released on 1983 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Network Analysis is a reference book on the methodology of network analysis -- the study of the structure of relations between people, groups or formal organizations. Illustrations from real research show the problems that arise in network analysis -- and how to resolve or avoid them. Primarily written by Burt and Minor, the book has the cohesion of a text while still using work from other leading network analysts.

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

Download or read book Advances in Social Network Analysis written by Stanley Wasserman and published by SAGE Publications. This book was released on 1994-07-27 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social network analysis, a method for analyzing relationships between social entities, has expanded over the last decade as new research has been done in this area. How can these new developments be applied effectively in the behavioral and social sciences disciplines? In Advances in Social Network Analysis, a team of leading methodologists in network analysis addresses this issue. They explore such topics as ways to specify the network contents to be studied, how to select the method for representing network structures, how social network analysis has been used to study interorganizational relations via the resource dependence model, how to use a contact matrix for studying the spread of disease in epidemiology, and how cohesion and structural equivalence network theories relate to studying social influence. It also offers statistical models for social support networks. Advances in Social Network Analysis is useful for researchers involved in general research methods and qualitative methods, and who are interested in psychology and sociology.

Download or read book A User s Guide to Network Analysis in R written by Douglas Luke and published by Springer. This book was released on 2015-12-14 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.

Download or read book Statistical and Machine Learning Approaches for Network Analysis written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2012-06-26 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networks An introduction to complex networks—measures, statistical properties, and models Modeling for evolving biological networks The structure of an evolving random bipartite graph Density-based enumeration in structured data Hyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.

Download or read book Social Networks Analysis and Case Studies written by Şule Gündüz-Öğüdücü and published by Springer. This book was released on 2014-07-11 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many opportunities in different application domains. Forming a bridge between theory and applications makes this work appealing to both academics and practitioners as well as graduate students.

Download or read book Statistical Analysis of Network Data with R written by Eric D. Kolaczyk and published by Springer. This book was released on 2014-05-22 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).

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.

Download or read book Social Network Analysis and Education written by Brian V. Carolan and published by SAGE Publications. This book was released on 2013-03-14 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social Network Analysis and Education: Theory, Methods & Applications provides an introduction to the theories, methods, and applications that constitute the social network perspective. Unlike more general texts, this applied title is designed for those current and aspiring educational researchers learning how to study, conceptualize, and analyze social networks. Brian V. Carolan's main intent is to encourage you to consider the social network perspective in light of your emerging research interests and evaluate how well this perspective illuminates the social complexities surrounding educational phenomena. Relying on diverse examples drawn from the educational research literature, this book makes explicit how the theories and methods associated with social network analysis can be used to better describe and explain the social complexities surrounding varied educational phenomena.