Information Security Analytics: Finding Security Insights, Patterns, and Anomalies in Big Data
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...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam [u.a.]
Syngress
2015
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Zusammenfassung: | 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 covere |
| Beschreibung: | XV, 166 S. Ill. |
| ISBN: | 9780128002070 |
Internformat
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
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| 008 | 150209s2015 a||| |||| 00||| eng d | ||
| 020 | |a 9780128002070 |9 978-0-12-800207-0 | ||
| 035 | |a (OCoLC)905352578 | ||
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| 100 | 1 | |a Talabis, Mark Ryan M. |e Verfasser |0 (DE-588)1029802572 |4 aut | |
| 245 | 1 | 0 | |a Information Security Analytics |b Finding Security Insights, Patterns, and Anomalies in Big Data |c Mark Ryan M. Talabis ... |
| 264 | 1 | |a Amsterdam [u.a.] |b Syngress |c 2015 | |
| 300 | |a XV, 166 S. |b Ill. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 520 | 1 | |a 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 covere | |
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| 999 | |a oai:aleph.bib-bvb.de:BVB01-027771795 | ||
Datensatz im Suchindex
| _version_ | 1804152942594359296 |
|---|---|
| adam_text | Contents
Foreword
...................................................................................................xi
About the Authors
....................................................................................xiii
Acknowledgments
....................................................................................xv
CHAPTER
1
ANALYTICS DEFINED
..........................................1
Introduction to Security Analytics
.......................................1
Concepts and Techniques in Analytics
................................2
General Statistics
..............................................................................2
Machine Learning
..............................................................................2
Supervised Learning
.........................................................................2
Unsupervised Learning
.....................................................................3
Simulations
........................................................................................4
Text Mining
........................................................................................4
Knowledge Engineering
....................................................................4
Data for Security Analytics
.................................................
A
Big Data
.............................................................................................5
Analytics in Everyday Life
...................................................7
Analytics insecurity
..........................................................................7
Analytics, Incident Response, and Intrusion Detection
....................7
Large and Diverse Data
.....................................................................7
Simulations and Security Processes
................................................8
Try Before You Buy
.............................................................................9
Simulation-Based Decisions
.............................................................9
Access Analytics
................................................................................9
Categorization and Classification in Vulnerability Management....
11
Security Analytics Process
...............................................12
References
.......................................................................12
Contents
CHAPTER
2
PRIMER ON ANALYTICAL SOFTWARE
ANU I UULw
■■■■■■·■■■■■···..........
m«
.....................
»i U
Introduction
......................................................................13
Statistical Programming
..................................................
U
Introduction to Databases and Big Data Techniques
.........15
Introduction to
R
...............................................................16
Assignment Operators
....................................................................18
Arithmetic Operators
.......................................................................18
Logical Operators
............................................................................18
Common
R
Functions
......................................................................19
Introduction to Python
......................................................19
Introduction to Simulation Software
.................................20
Designing and Creating the Model
..................................................21
Adding Data and Parameters to the Model
.....................................21
Running the Simulation
...................................................................21
Analyzing the Simulation
.................................................................22
References
.......................................................................22
CHAPTER
3
ANALYTICS AND INCIDENT RESPONSE
.............23
Introduction
......................................................................23
Scenarios and Challenges in Intrusions and Incident
Identification
....................................................................24
Analyzing a Collection of Server Logs with Big Data
......................25
Analysis of Log Files
.........................................................25
Common Log File Fields
.................................................................26
Combined Log File Fields
................................................................26
Methods
...........................................................................................26
Additional Data and Software Needed to Run these Examples
......26
Loading the Data
...............................................................27
Discovery Process for Specific Attack Vectors
................................30
SQL Injection Attack
........................................................................30
Directory Traversal and File Inclusion
............................................32
Cross-site Request Forgery
............................................................35
Command Injection
.............................................................
3¿
MySQL Charset Switch and MS-SQL DoS Attack
............................37
Contents
Tallying and Tracking Failed Request Statuses
..............................39
Hosts with the most Failed Requests
.............................................39
Bot
Activity
.......................................................................................43
Time Aggregations
..........................................................................
Д5
Hosts with the most Failed Requests per day, or per month
.........47
Failed Requests Presented as a Monthly Time Series
...................
Д8
Ratio of Failed to Successful Requests as a Time Series
...............
Д9
Hive for Producing Analytical Data Sets
.........................................56
Another Potential Analytical Data Set: Unstacked
Status Codes
.....................................................................59
Other Applicable Security Areas and Scenarios
...............64
Summary
..........................................................................64
Further Reading
...............................................................65
CHAPTER
4
SIMULATIONS AND SECURITY PROCESSES
.......67
Simulation
........................................................................67
Designing and Creating a Model
.....................................................68
Adding Data and
Parametersto
the Model
.....................................69
Running the Simulation
...................................................................69
Analyzing the Simulation
.................................................................69
Casestudy
........................................................................69
CHAPTER
5
ACCESS ANALYTICS
..........................................99
Introduction
......................................................................99
Technology Primer
.........................................................100
Remote Access and VPN
...............................................................100
Python and Scripting
.....................................................................102
Scenario, Analysis, and Techniques
................................104
Problem
.........................................................................................
Ш
Data Collection
..............................................................................105
Data Analysis
.................................................................................105
Data Processing
.............................................................................108
Casestudy
......................................................................109
Importing What You Need
..............................................................109
Program Flow
................................................................................111
Parse the Arguments
....................................................................112
Read the VPN Logs
........................................................................112
Normalize the Event Data from the VPN logs
...............................113
Run the Analytics
...........................................................................115
Analyzing the Results
.....................................................117
CHAPTER
6
SECURITY AND TEXT MINING
..........................123
Scenarios and Challenges in Security Analytics
with Text Mining
.............................................................123
Use of Text Mining Techniques to Analyze and Find
Patterns in Unstructured Data
........................................124
Text Mining Basics
.........................................................................124
Common Data Transformations for Text Mining
...........................125
Step by Step Text Mining Example in
R
...........................125
R
Code Walk-through
....................................................................126
Other Applicable Security Areas and Scenarios
.............
U7
Additional Security Scenarios for Text Mining
..............................
U8
Text Mining and Big Data
...............................................................
U9
CHAPTER
7
SECURITY INTELLIGENCE AND NEXT STEPS.....
151
Overview
.........................................................................151
Security Intelligence
......................................................151
Basic Security Intelligence Analysis
.............................................152
Business Extension of Security Analytics
.....................................154
Security Breaches
..........................................................154
Practical Application
......................................................155
Insider Threat
................................................................................155
Resource Justification
...................................................................156
Risk Management
..........................................................................157
Challenges
.....................................................................................158
False Positives
...............................................................................160
Concluding Remarks
......................................................160
|
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| discipline | Informatik |
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| id | DE-604.BV042335149 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T01:18:44Z |
| institution | BVB |
| isbn | 9780128002070 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027771795 |
| oclc_num | 905352578 |
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| owner_facet | DE-473 DE-BY-UBG |
| physical | XV, 166 S. Ill. |
| publishDate | 2015 |
| publishDateSearch | 2015 |
| publishDateSort | 2015 |
| publisher | Syngress |
| record_format | marc |
| spelling | Talabis, Mark Ryan M. Verfasser (DE-588)1029802572 aut Information Security Analytics Finding Security Insights, Patterns, and Anomalies in Big Data Mark Ryan M. Talabis ... Amsterdam [u.a.] Syngress 2015 XV, 166 S. Ill. txt rdacontent n rdamedia nc rdacarrier 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 covere Datensicherung (DE-588)4011144-1 gnd rswk-swf Big Data (DE-588)4802620-7 gnd rswk-swf Big Data (DE-588)4802620-7 s Datensicherung (DE-588)4011144-1 s DE-604 Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027771795&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Talabis, Mark Ryan M. Information Security Analytics Finding Security Insights, Patterns, and Anomalies in Big Data Datensicherung (DE-588)4011144-1 gnd Big Data (DE-588)4802620-7 gnd |
| subject_GND | (DE-588)4011144-1 (DE-588)4802620-7 |
| title | Information Security Analytics Finding Security Insights, Patterns, and Anomalies in Big Data |
| title_auth | Information Security Analytics Finding Security Insights, Patterns, and Anomalies in Big Data |
| title_exact_search | Information Security Analytics Finding Security Insights, Patterns, and Anomalies in Big Data |
| title_full | Information Security Analytics Finding Security Insights, Patterns, and Anomalies in Big Data Mark Ryan M. Talabis ... |
| title_fullStr | Information Security Analytics Finding Security Insights, Patterns, and Anomalies in Big Data Mark Ryan M. Talabis ... |
| title_full_unstemmed | Information Security Analytics Finding Security Insights, Patterns, and Anomalies in Big Data Mark Ryan M. Talabis ... |
| title_short | Information Security Analytics |
| title_sort | information security analytics finding security insights patterns and anomalies in big data |
| title_sub | Finding Security Insights, Patterns, and Anomalies in Big Data |
| topic | Datensicherung (DE-588)4011144-1 gnd Big Data (DE-588)4802620-7 gnd |
| topic_facet | Datensicherung Big Data |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027771795&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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