<p><i>Information Security Analytics</i> 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.</p><p><i>Information Security
Information Security Analytics: Finding Security Insights, Patterns, and Anomalies in Big Data
โ Scribed by Mark Talabis, Robert McPherson, Inez Miyamoto, Jason Martin
- Publisher
- Syngress
- Year
- 2014
- Tongue
- English
- Leaves
- 183
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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.
โฆ Table of Contents
Front Cover
Information Security Analytics: Finding Security Insights, Patterns, and Anomalies in Big Data
Copyright
Dedication
Contents
Foreword
About the Authors
Acknowledgments
Chapter 1 - Analytics Defined
INTRODUCTION TO SECURITY ANALYTICS
CONCEPTS AND TECHNIQUES IN ANALYTICS
DATA FOR SECURITY ANALYTICS
ANALYTICS IN EVERYDAY LIFE
SECURITY ANALYTICS PROCESS
REFERENCES
Chapter 2 - Primer on Analytical Software and Tools
STATISTICAL PROGRAMMING
INTRODUCTION TO DATABASES AND BIG DATA TECHNIQUES
REFERENCES
Chapter 3 - Analytics and Incident Response
INTRODUCTION
SCENARIOS AND CHALLENGES IN INTRUSIONS AND INCIDENT IDENTIFICATION
ANALYSIS OF LOG FILES
LOADING THE DATA
ANOTHER POTENTIAL ANALYTICAL DATA SET: UNSTACKED STATUS CODES
OTHER APPLICABLE SECURITY AREAS AND SCENARIOS
SUMMARY
FURTHER READING
Chapter 4 - Simulations and Security Processes
SIMULATION
CASE STUDY
Chapter 5 - Access Analytics
INTRODUCTION
TECHNOLOGY PRIMER
SCENARIO, ANALYSIS, AND TECHNIQUES
CASE STUDY
ANALYZING THE RESULTS
Chapter 6 - Security and Text Mining
SCENARIOS AND CHALLENGES IN SECURITY ANALYTICS WITH TEXT MINING
USE OF TEXT MINING TECHNIQUES TO ANALYZE AND FIND PATTERNS IN UNSTRUCTURED DATA
STEP BY STEP TEXT MINING EXAMPLE IN R
OTHER APPLICABLE SECURITY AREAS AND SCENARIOS
Chapter 7 - Security Intelligence and Next Steps
OVERVIEW
SECURITY INTELLIGENCE
SECURITY BREACHES
PRACTICAL APPLICATION
CONCLUDING REMARKS
Index
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