Network Intrusion Analysis

Network Intrusion Analysis addresses the entire process of investigating a network intrusion by: Providing a step-by-step guide to the tools and techniques used in the analysis and investigation of a network intrusion. Providing real-world examples of network intrusions, along with associated workarounds. Walking you through the methodology and practical steps needed to conduct a thorough intrusion investigation and incident response, including a wealth of practical, hands-on tools for incident assessment and mitigation. Network Intrusion Analysis addresses the entire process of investigating a network intrusion. Provides a step-by-step guide to the tools and techniques used in the analysis and investigation of a network intrusion. Provides real-world examples of network intrusions, along with associated workarounds.

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

“Practical Intrusion Analysis provides a solid fundamental overview of the art and science of intrusion analysis.” –Nate Miller, Cofounder, Stratum Security The Only Definitive Guide to New State-of-the-Art Techniques in Intrusion Detection and Prevention Recently, powerful innovations in intrusion detection and prevention have evolved in response to emerging threats and changing business environments. However, security practitioners have found little reliable, usable information about these new IDS/IPS technologies. In Practical Intrusion Analysis, one of the field’s leading experts brings together these innovations for the first time and demonstrates how they can be used to analyze attacks, mitigate damage, and track attackers. Ryan Trost reviews the fundamental techniques and business drivers of intrusion detection and prevention by analyzing today’s new vulnerabilities and attack vectors. Next, he presents complete explanations of powerful new IDS/IPS methodologies based on Network Behavioral Analysis (NBA), data visualization, geospatial analysis, and more. Writing for security practitioners and managers at all experience levels, Trost introduces new solutions for virtually every environment. Coverage includes Assessing the strengths and limitations of mainstream monitoring tools and IDS technologies Using Attack Graphs to map paths of network vulnerability and becoming more proactive about preventing intrusions Analyzing network behavior to immediately detect polymorphic worms, zero-day exploits, and botnet DoS attacks Understanding the theory, advantages, and disadvantages of the latest Web Application Firewalls Implementing IDS/IPS systems that protect wireless data traffic Enhancing your intrusion detection efforts by converging with physical security defenses Identifying attackers’ “geographical fingerprints” and using that information to respond more effectively Visualizing data traffic to identify suspicious patterns more quickly Revisiting intrusion detection ROI in light of new threats, compliance risks, and technical alternatives Includes contributions from these leading network security experts: Jeff Forristal, a.k.a. Rain Forest Puppy, senior security professional and creator of libwhisker Seth Fogie, CEO, Airscanner USA; leading-edge mobile security researcher; coauthor of Security Warrior Dr. Sushil Jajodia, Director, Center for Secure Information Systems; founding Editor-in-Chief, Journal of Computer Security Dr. Steven Noel, Associate Director and Senior Research Scientist, Center for Secure Information Systems, George Mason University Alex Kirk, Member, Sourcefire Vulnerability Research Team

Network Intrusion Detection and Prevention: Concepts and Techniques provides detailed and concise information on different types of attacks, theoretical foundation of attack detection approaches, implementation, data collection, evaluation, and intrusion response. Additionally, it provides an overview of some of the commercially/publicly available intrusion detection and response systems. On the topic of intrusion detection system it is impossible to include everything there is to say on all subjects. However, we have tried to cover the most important and common ones. Network Intrusion Detection and Prevention: Concepts and Techniques is designed for researchers and practitioners in industry. This book is suitable for advanced-level students in computer science as a reference book as well.

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

There is increasing pressure to protect computer networks against unauthorized intrusion, and some work in this area is concerned with engineering systems that are robust to attack. However, no system can be made invulnerable. Data Analysis for Network Cyber-Security focuses on monitoring and analyzing network traffic data, with the intention of preventing, or quickly identifying, malicious activity. Such work involves the intersection of statistics, data mining and computer science. Fundamentally, network traffic is relational, embodying a link between devices. As such, graph analysis approaches are a natural candidate. However, such methods do not scale well to the demands of real problems, and the critical aspect of the timing of communications events is not accounted for in these approaches. This book gathers papers from leading researchers to provide both background to the problems and a description of cutting-edge methodology. The contributors are from diverse institutions and areas of expertise and were brought together at a workshop held at the University of Bristol in March 2013 to address the issues of network cyber security. The workshop was supported by the Heilbronn Institute for Mathematical Research. Contents:Inference for Graphs and Networks: Adapting Classical Tools to Modern Data (Benjamin P Olding and Patrick J Wolfe)Rapid Detection of Attacks in Computer Networks by Quickest Changepoint Detection Methods (Alexander G Tartakovsky)Statistical Detection of Intruders Within Computer Networks Using Scan Statistics (Joshua Neil, Curtis Storlie, Curtis Hash and Alex Brugh)Characterizing Dynamic Group Behavior in Social Networks for Cybernetics (Sumeet Dua and Pradeep Chowriappa)Several Approaches for Detecting Anomalies in Network Traffic Data (Céline Lévy-Leduc)Monitoring a Device in a Communication Network (Nicholas A Heard and Melissa Turcotte) Readership: Researchers and graduate students in the fields of network traffic data analysis and network cyber security. Key Features:This book is unique in being a treatise on the statistical analysis of network traffic dataThe contributors are leading researches in the field and will give authoritative descriptions of cutting edge methodologyThe book features material from diverse areas, and as such forms a unified view of network cyber securityKeywords:Network Data Analysis;Cyber Security;Change Detection;Anomaly Detection

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