Network Security Through Data Analysis

Building Situational Awareness
Author: Michael S Collins
Publisher: "O'Reilly Media, Inc."
ISBN: 1449357865
Category: Computers
Page: 348
View: 6567

Continue Reading →

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

From Data to Action
Author: Michael Collins
Publisher: "O'Reilly Media, Inc."
ISBN: 149196281X
Category: Computers
Page: 428
View: 4178

Continue Reading →

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

Analysis, Visualization and Dashboards
Author: Jay Jacobs,Bob Rudis
Publisher: John Wiley & Sons
ISBN: 111879382X
Category: Computers
Page: 352
View: 5227

Continue Reading →

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.

Applied Network Security Monitoring

Collection, Detection, and Analysis
Author: Chris Sanders,Jason Smith
Publisher: Elsevier
ISBN: 0124172164
Category: Computers
Page: 496
View: 3732

Continue Reading →

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 Analysis for Network Cyber-Security


Author: Niall Adams,Nicholas Heard
Publisher: World Scientific
ISBN: 1783263768
Category: Computers
Page: 200
View: 5725

Continue Reading →

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

Machine Learning and Security

Protecting Systems with Data and Algorithms
Author: Clarence Chio,David Freeman
Publisher: "O'Reilly Media, Inc."
ISBN: 1491979852
Category: Computers
Page: 386
View: 9347

Continue Reading →

Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself! With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions

Data Mining and Machine Learning in Cybersecurity


Author: Sumeet Dua,Xian Du
Publisher: CRC Press
ISBN: 9781439839430
Category: Computers
Page: 256
View: 4537

Continue Reading →

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.

Network Anomaly Detection

A Machine Learning Perspective
Author: Dhruba Kumar Bhattacharyya,Jugal Kumar Kalita
Publisher: CRC Press
ISBN: 146658209X
Category: Computers
Page: 366
View: 3823

Continue Reading →

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.

Information Security Risk Assessment Toolkit

Practical Assessments Through Data Collection and Data Analysis
Author: Mark Talabis,Jason Martin
Publisher: Newnes
ISBN: 1597497355
Category: Computers
Page: 258
View: 1271

Continue Reading →

In order to protect company's information assets such as sensitive customer records, health care records, etc., the security practitioner first needs to find out: what needs protected, what risks those assets are exposed to, what controls are in place to offset those risks, and where to focus attention for risk treatment. This is the true value and purpose of information security risk assessments. Effective risk assessments are meant to provide a defendable analysis of residual risk associated with your key assets so that risk treatment options can be explored. Information Security Risk Assessments gives you the tools and skills to get a quick, reliable, and thorough risk assessment for key stakeholders. Based on authors' experiences of real-world assessments, reports, and presentations Focuses on implementing a process, rather than theory, that allows you to derive a quick and valuable assessment Includes a companion web site with spreadsheets you can utilize to create and maintain the risk assessment

Information Security Analytics

Finding Security Insights, Patterns, and Anomalies in Big Data
Author: Mark Talabis,Robert McPherson,Inez Miyamoto,Jason Martin
Publisher: Syngress
ISBN: 0128005068
Category: Computers
Page: 182
View: 1509

Continue Reading →

Information Security Analytics gives you insights into the practice of analytics and, more importantly, how you can utilize analytic techniques to identify trends and outliers that may not be possible to identify using traditional security analysis techniques. Information Security Analytics dispels the myth that analytics within the information security domain is limited to just security incident and event management systems and basic network analysis. Analytic techniques can help you mine data and identify patterns and relationships in any form of security data. Using the techniques covered in this book, you will be able to gain security insights into unstructured big data of any type. The authors of Information Security Analytics bring a wealth of analytics experience to demonstrate practical, hands-on techniques through case studies and using freely-available tools that will allow you to find anomalies and outliers by combining disparate data sets. They also teach you everything you need to know about threat simulation techniques and how to use analytics as a powerful decision-making tool to assess security control and process requirements within your organization. Ultimately, you will learn how to use these simulation techniques to help predict and profile potential risks to your organization. Written by security practitioners, for security practitioners Real-world case studies and scenarios are provided for each analytics technique Learn about open-source analytics and statistical packages, tools, and applications Step-by-step guidance on how to use analytics tools and how they map to the techniques and scenarios provided Learn how to design and utilize simulations for "what-if" scenarios to simulate security events and processes Learn how to utilize big data techniques to assist in incident response and intrusion analysis

The Practice of Network Security Monitoring

Understanding Incident Detection and Response
Author: Richard Bejtlich
Publisher: No Starch Press
ISBN: 159327534X
Category: Computers
Page: 376
View: 624

Continue Reading →

Network security is not simply about building impenetrable walls—determined attackers will eventually overcome traditional defenses. The most effective computer security strategies integrate network security monitoring (NSM): the collection and analysis of data to help you detect and respond to intrusions. In The Practice of Network Security Monitoring, Mandiant CSO Richard Bejtlich shows you how to use NSM to add a robust layer of protection around your networks—no prior experience required. To help you avoid costly and inflexible solutions, he teaches you how to deploy, build, and run an NSM operation using open source software and vendor-neutral tools. You'll learn how to: –Determine where to deploy NSM platforms, and size them for the monitored networks –Deploy stand-alone or distributed NSM installations –Use command line and graphical packet analysis tools, and NSM consoles –Interpret network evidence from server-side and client-side intrusions –Integrate threat intelligence into NSM software to identify sophisticated adversaries There’s no foolproof way to keep attackers out of your network. But when they get in, you’ll be prepared. The Practice of Network Security Monitoring will show you how to build a security net to detect, contain, and control them. Attacks are inevitable, but losing sensitive data shouldn't be.

Cyber Security: Analytics, Technology and Automation


Author: Martti Lehto,Pekka Neittaanmäki
Publisher: Springer
ISBN: 3319183028
Category: Computers
Page: 269
View: 4112

Continue Reading →

The book, in addition to the cyber threats and technology, processes cyber security from many sides as a social phenomenon and how the implementation of the cyber security strategy is carried out. The book gives a profound idea of the most spoken phenomenon of this time. The book is suitable for a wide-ranging audience from graduate to professionals/practitioners and researchers. Relevant disciplines for the book are Telecommunications / Network security, Applied mathematics / Data analysis, Mobile systems / Security, Engineering / Security of critical infrastructure and Military science / Security.

Applied Security Visualization


Author: Raffael Marty
Publisher: Addison-Wesley Professional
ISBN: 9780321510105
Category: Computers
Page: 523
View: 2029

Continue Reading →

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.

Security Data Visualization

Graphical Techniques for Network Analysis
Author: Greg Conti
Publisher: No Starch Press
ISBN: 1593271433
Category: Computers
Page: 272
View: 5195

Continue Reading →

An introduction to a range of cyber security issues explains how to utilize graphical approaches to displaying and understanding computer security data, such as network traffic, server logs, and executable files, offering guidelines for identifying a network attack, how to assess a system for vulnerabilities with Afterglow and RUMINT visualization software, and how to protect a system from additional attacks. Original. (Intermediate)

Network Traffic Anomaly Detection and Prevention

Concepts, Techniques, and Tools
Author: Monowar H. Bhuyan,Dhruba K. Bhattacharyya,Jugal K. Kalita
Publisher: Springer
ISBN: 3319651889
Category: Computers
Page: 263
View: 4886

Continue Reading →

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.

Application of Big Data for National Security

A Practitioner’s Guide to Emerging Technologies
Author: Babak Akhgar,Gregory B. Saathoff,Hamid R Arabnia,Richard Hill,Andrew Staniforth,Petra Saskia Bayerl
Publisher: Butterworth-Heinemann
ISBN: 0128019735
Category: Political Science
Page: 316
View: 8505

Continue Reading →

Application of Big Data for National Security provides users with state-of-the-art concepts, methods, and technologies for Big Data analytics in the fight against terrorism and crime, including a wide range of case studies and application scenarios. This book combines expertise from an international team of experts in law enforcement, national security, and law, as well as computer sciences, criminology, linguistics, and psychology, creating a unique cross-disciplinary collection of knowledge and insights into this increasingly global issue. The strategic frameworks and critical factors presented in Application of Big Data for National Security consider technical, legal, ethical, and societal impacts, but also practical considerations of Big Data system design and deployment, illustrating how data and security concerns intersect. In identifying current and future technical and operational challenges it supports law enforcement and government agencies in their operational, tactical and strategic decisions when employing Big Data for national security Contextualizes the Big Data concept and how it relates to national security and crime detection and prevention Presents strategic approaches for the design, adoption, and deployment of Big Data technologies in preventing terrorism and reducing crime Includes a series of case studies and scenarios to demonstrate the application of Big Data in a national security context Indicates future directions for Big Data as an enabler of advanced crime prevention and detection

Sharing Big Data Safely

Managing Data Security
Author: Ted Dunning,Ellen Friedman
Publisher: "O'Reilly Media, Inc."
ISBN: 1491953632
Category: Computers
Page: 96
View: 1603

Continue Reading →

Many big data-driven companies today are moving to protect certain types of data against intrusion, leaks, or unauthorized eyes. But how do you lock down data while granting access to people who need to see it? In this practical book, authors Ted Dunning and Ellen Friedman offer two novel and practical solutions that you can implement right away. Ideal for both technical and non-technical decision makers, group leaders, developers, and data scientists, this book shows you how to: Share original data in a controlled way so that different groups within your organization only see part of the whole. You’ll learn how to do this with the new open source SQL query engine Apache Drill. Provide synthetic data that emulates the behavior of sensitive data. This approach enables external advisors to work with you on projects involving data that you can't show them. If you’re intrigued by the synthetic data solution, explore the log-synth program that Ted Dunning developed as open source code (available on GitHub), along with how-to instructions and tips for best practice. You’ll also get a collection of use cases. Providing lock-down security while safely sharing data is a significant challenge for a growing number of organizations. With this book, you’ll discover new options to share data safely without sacrificing security.

Network Security Technologies: Design and Applications

Design and Applications
Author: Amine, Abdelmalek
Publisher: IGI Global
ISBN: 1466647906
Category: Computers
Page: 330
View: 8716

Continue Reading →

Recent advances in technologies have created a need for solving security problems in a systematic way. With this in mind, network security technologies have been produced in order to ensure the security of software and communication functionalities at basic, enhanced, and architectural levels. Network Security Technologies: Design and Applications presents theoretical frameworks and the latest research findings in network security technologies while analyzing malicious threats which can compromise network integrity. This book is an essential tool for researchers and professionals interested in improving their understanding of the strategic role of trust at different levels of information and knowledge society.

Network Security with Netflow and IPFIX

Big Data Analytics for Information Security
Author: Omar Santos
Publisher: Cisco Press
ISBN: 0134033523
Category: Computers
Page: 320
View: 384

Continue Reading →

A comprehensive guide for deploying, configuring, and troubleshooting NetFlow and learning big data analytics technologies for cyber security Today’s world of network security is full of cyber security vulnerabilities, incidents, breaches, and many headaches. Visibility into the network is an indispensable tool for network and security professionals and Cisco NetFlow creates an environment where network administrators and security professionals have the tools to understand who, what, when, where, and how network traffic is flowing. Network Security with NetFlow and IPFIX is a key resource for introducing yourself to and understanding the power behind the Cisco NetFlow solution. Omar Santos, a Cisco Product Security Incident Response Team (PSIRT) technical leader and author of numerous books including the CCNA Security 210-260 Official Cert Guide, details the importance of NetFlow and demonstrates how it can be used by large enterprises and small-to-medium-sized businesses to meet critical network challenges. This book also examines NetFlow’s potential as a powerful network security tool. Network Security with NetFlow and IPFIX explores everything you need to know to fully understand and implement the Cisco Cyber Threat Defense Solution. It also provides detailed configuration and troubleshooting guidance, sample configurations with depth analysis of design scenarios in every chapter, and detailed case studies with real-life scenarios. You can follow Omar on Twitter: @santosomar NetFlow and IPFIX basics Cisco NetFlow versions and features Cisco Flexible NetFlow NetFlow Commercial and Open Source Software Packages Big Data Analytics tools and technologies such as Hadoop, Flume, Kafka, Storm, Hive, HBase, Elasticsearch, Logstash, Kibana (ELK) Additional Telemetry Sources for Big Data Analytics for Cyber Security Understanding big data scalability Big data analytics in the Internet of everything Cisco Cyber Threat Defense and NetFlow Troubleshooting NetFlow Real-world case studies

Learn Data Analysis with Python

Lessons in Coding
Author: A.J. Henley,Dave Wolf
Publisher: Apress
ISBN: 1484234863
Category: Computers
Page: 97
View: 8239

Continue Reading →

Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting data in and out of Python code in the right format. Learn Data Analysis with Python also helps you discover meaning in the data using analysis and shows you how to visualize it. Each lesson is, as much as possible, self-contained to allow you to dip in and out of the examples as your needs dictate. If you are already using Python for data analysis, you will find a number of things that you wish you knew how to do in Python. You can then take these techniques and apply them directly to your own projects. If you aren’t using Python for data analysis, this book takes you through the basics at the beginning to give you a solid foundation in the topic. As you work your way through the book you will have a better of idea of how to use Python for data analysis when you are finished. What You Will Learn Get data into and out of Python code Prepare the data and its format Find the meaning of the data Visualize the data using iPython Who This Book Is For Those who want to learn data analysis using Python. Some experience with Python is recommended but not required, as is some prior experience with data analysis or data science.