Network Security Through Data Analysis

Author: Michael Collins
Publisher: "O'Reilly Media, Inc."
ISBN: 1449357881
Format: PDF, Kindle
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Traditional intrusion detection and logfile analysis are no longer enough to protect today’s complex networks. In this practical guide, security researcher Michael Collins shows you several techniques and tools for collecting and analyzing network traffic datasets. You’ll understand how your network is used, and what actions are necessary to protect and improve it. Divided into three sections, this book examines the process of collecting and organizing data, various tools for analysis, and several different analytic scenarios and techniques. It’s ideal for network administrators and operational security analysts familiar with scripting. Explore network, host, and service sensors for capturing security data Store data traffic with relational databases, graph databases, Redis, and Hadoop Use SiLK, the R language, and other tools for analysis and visualization Detect unusual phenomena through Exploratory Data Analysis (EDA) Identify significant structures in networks with graph analysis Determine the traffic that’s crossing service ports in a network Examine traffic volume and behavior to spot DDoS and database raids Get a step-by-step process for network mapping and inventory

Network Security Through Data Analysis

Author: Michael S Collins
Publisher: "O'Reilly Media, Inc."
ISBN: 1449357865
Format: PDF, ePub, Mobi
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Traditional intrusion detection and logfile analysis are no longer enough to protect today’s complex networks. In this practical guide, security researcher Michael Collins shows you several techniques and tools for collecting and analyzing network traffic datasets. You’ll understand how your network is used, and what actions are necessary to protect and improve it. Divided into three sections, this book examines the process of collecting and organizing data, various tools for analysis, and several different analytic scenarios and techniques. It’s ideal for network administrators and operational security analysts familiar with scripting. Explore network, host, and service sensors for capturing security data Store data traffic with relational databases, graph databases, Redis, and Hadoop Use SiLK, the R language, and other tools for analysis and visualization Detect unusual phenomena through Exploratory Data Analysis (EDA) Identify significant structures in networks with graph analysis Determine the traffic that’s crossing service ports in a network Examine traffic volume and behavior to spot DDoS and database raids Get a step-by-step process for network mapping and inventory

Network Security Through Data Analysis

Author: Michael Collins
Publisher: O'Reilly Media
ISBN: 9781449357900
Format: PDF, Kindle
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Discusses techniques for collecting, organizing, and analyzing network traffic data, covering such topics as data fusion; using SiLK, R, and Python; network mapping and inventory; and handling malware.

Network Security Through Data Analysis

Author: Michael Collins
Publisher: "O'Reilly Media, Inc."
ISBN: 149196281X
Format: PDF, ePub, Mobi
Download Now
Traditional intrusion detection and logfile analysis are no longer enough to protect today’s complex networks. In the updated second edition of this practical guide, security researcher Michael Collins shows InfoSec personnel the latest techniques and tools for collecting and analyzing network traffic datasets. You’ll understand how your network is used, and what actions are necessary to harden and defend the systems within it. In three sections, this book examines the process of collecting and organizing data, various tools for analysis, and several different analytic scenarios and techniques. New chapters focus on active monitoring and traffic manipulation, insider threat detection, data mining, regression and machine learning, and other topics. You’ll learn how to: Use sensors to collect network, service, host, and active domain data Work with the SiLK toolset, Python, and other tools and techniques for manipulating data you collect Detect unusual phenomena through exploratory data analysis (EDA), using visualization and mathematical techniques Analyze text data, traffic behavior, and communications mistakes Identify significant structures in your network with graph analysis Examine insider threat data and acquire threat intelligence Map your network and identify significant hosts within it Work with operations to develop defenses and analysis techniques

Data Driven Security

Author: Jay Jacobs
Publisher: John Wiley & Sons
ISBN: 111879382X
Format: PDF, ePub, Docs
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Uncover hidden patterns of data and respond with countermeasures Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful ? data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions. Everything in this book will have practical application for information security professionals. Helps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks Includes more than a dozen real-world examples and hands-on exercises that demonstrate how to analyze security data and intelligence and translate that information into visualizations that make plain how to prevent attacks Covers topics such as how to acquire and prepare security data, use simple statistical methods to detect malware, predict rogue behavior, correlate security events, and more Written by a team of well-known experts in the field of security and data analysis Lock down your networks, prevent hacks, and thwart malware by improving visibility into the environment, all through the power of data and Security Using Data Analysis, Visualization, and Dashboards.

Network Anomaly Detection

Author: Dhruba Kumar Bhattacharyya
Publisher: CRC Press
ISBN: 146658209X
Format: PDF, ePub, Docs
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With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavior. Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents machine learning techniques in depth to help you more effectively detect and counter network intrusion. In this book, you’ll learn about: Network anomalies and vulnerabilities at various layers The pros and cons of various machine learning techniques and algorithms A taxonomy of attacks based on their characteristics and behavior Feature selection algorithms How to assess the accuracy, performance, completeness, timeliness, stability, interoperability, reliability, and other dynamic aspects of a network anomaly detection system Practical tools for launching attacks, capturing packet or flow traffic, extracting features, detecting attacks, and evaluating detection performance Important unresolved issues and research challenges that need to be overcome to provide better protection for networks Examining numerous attacks in detail, the authors look at the tools that intruders use and show how to use this knowledge to protect networks. The book also provides material for hands-on development, so that you can code on a testbed to implement detection methods toward the development of your own intrusion detection system. It offers a thorough introduction to the state of the art in network anomaly detection using machine learning approaches and systems.

Applied Network Security Monitoring

Author: Chris Sanders
Publisher: Elsevier
ISBN: 0124172164
Format: PDF, ePub, Docs
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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

Data Mining and Machine Learning in Cybersecurity

Author: Sumeet Dua
Publisher: CRC Press
ISBN: 9781439839430
Format: PDF, Docs
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With the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity. Although several conferences, workshops, and journals focus on the fragmented research topics in this area, there has been no single interdisciplinary resource on past and current works and possible paths for future research in this area. This book fills this need. From basic concepts in machine learning and data mining to advanced problems in the machine learning domain, Data Mining and Machine Learning in Cybersecurity provides a unified reference for specific machine learning solutions to cybersecurity problems. It supplies a foundation in cybersecurity fundamentals and surveys contemporary challenges—detailing cutting-edge machine learning and data mining techniques. It also: Unveils cutting-edge techniques for detecting new attacks Contains in-depth discussions of machine learning solutions to detection problems Categorizes methods for detecting, scanning, and profiling intrusions and anomalies Surveys contemporary cybersecurity problems and unveils state-of-the-art machine learning and data mining solutions Details privacy-preserving data mining methods This interdisciplinary resource includes technique review tables that allow for speedy access to common cybersecurity problems and associated data mining methods. Numerous illustrative figures help readers visualize the workflow of complex techniques and more than forty case studies provide a clear understanding of the design and application of data mining and machine learning techniques in cybersecurity.

Logging and Log Management

Author: Anton Chuvakin
Publisher: Newnes
ISBN: 1597496367
Format: PDF, Kindle
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Logging and Log Management: The Authoritative Guide to Understanding the Concepts Surrounding Logging and Log Management introduces information technology professionals to the basic concepts of logging and log management. It provides tools and techniques to analyze log data and detect malicious activity. The book consists of 22 chapters that cover the basics of log data; log data sources; log storage technologies; a case study on how syslog-ng is deployed in a real environment for log collection; covert logging; planning and preparing for the analysis log data; simple analysis techniques; and tools and techniques for reviewing logs for potential problems. The book also discusses statistical analysis; log data mining; visualizing log data; logging laws and logging mistakes; open source and commercial toolsets for log data collection and analysis; log management procedures; and attacks against logging systems. In addition, the book addresses logging for programmers; logging and compliance with regulations and policies; planning for log analysis system deployment; cloud logging; and the future of log standards, logging, and log analysis. This book was written for anyone interested in learning more about logging and log management. These include systems administrators, junior security engineers, application developers, and managers. Comprehensive coverage of log management including analysis, visualization, reporting and more Includes information on different uses for logs -- from system operations to regulatory compliance Features case Studies on syslog-ng and actual real-world situations where logs came in handy in incident response Provides practical guidance in the areas of report, log analysis system selection, planning a log analysis system and log data normalization and correlation

Applied Security Visualization

Author: Raffael Marty
Publisher: Addison-Wesley Professional
ISBN: 9780321510105
Format: PDF
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Harness new techniques that let you see what is happening on your networks and take decisive action without getting lost in a sea of data.