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Network Security Through Data Analysis Building Situational Awareness 1st Edition by Michael Collins ISBN 1449357903 9781449357900

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Network Security Through Data Analysis Building Situational Awareness 1st Edition Michael Collins Digital Instant Download

Author(s): Michael Collins
ISBN(s): 9781449357900, 1449357903
Edition: 1
File Details: PDF, 13.49 MB
Year: 2014
Language: english
SKU: EB-4657952 Category: Tag:

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ISBN 10: 1449357903 
ISBN 13: 9781449357900
Author: Michael Collins

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 dataStore data traffic with relational databases, graph databases, Redis, and HadoopUse SiLK, the R language, and other tools for analysis and visualizationDetect unusual phenomena through Exploratory Data Analysis (EDA)Identify significant structures in networks with graph analysisDetermine the traffic that’s crossing service ports in a networkExamine traffic volume and behavior to spot DDoS and database raidsGet a step-by-step process for network mapping and inventory

Network Security Through Data Analysis Building Situational Awareness 1st Table of contents:

Part I: Introduction to Network Security and Data Analysis

  • Chapter 1: Introduction to Network Security

    • 1.1 The Growing Importance of Network Security

    • 1.2 Network Security Threats and Vulnerabilities

    • 1.3 Key Concepts in Network Security

    • 1.4 The Role of Data Analysis in Security

  • Chapter 2: Understanding Situational Awareness

    • 2.1 Definition and Importance of Situational Awareness in Cybersecurity

    • 2.2 The Components of Situational Awareness

    • 2.3 Situational Awareness in the Context of Network Security

    • 2.4 Benefits of Building Situational Awareness

Part II: Core Concepts of Data Analysis in Network Security

  • Chapter 3: Data Collection and Preprocessing

    • 3.1 Types of Network Data (Logs, Traffic, Events)

    • 3.2 Techniques for Data Collection

    • 3.3 Data Preprocessing and Cleaning Techniques

    • 3.4 Data Formats and Standardization

    • 3.5 Integrating Data from Multiple Sources

  • Chapter 4: Analyzing Network Data

    • 4.1 Descriptive and Diagnostic Analysis

    • 4.2 Pattern Recognition and Anomaly Detection

    • 4.3 Using Machine Learning for Threat Detection

    • 4.4 Statistical Methods in Network Security

    • 4.5 Identifying Attacks through Data Analysis

  • Chapter 5: Building and Visualizing Network Security Dashboards

    • 5.1 Key Metrics for Security Situational Awareness

    • 5.2 Designing Effective Dashboards for Monitoring

    • 5.3 Real-time Data Visualization Techniques

    • 5.4 Integrating Threat Intelligence Feeds

    • 5.5 Using Dashboards for Rapid Decision Making

Part III: Threat Detection and Mitigation

  • Chapter 6: Intrusion Detection Systems (IDS) and Network Monitoring

    • 6.1 Types of Intrusion Detection Systems (Signature-based, Anomaly-based, Hybrid)

    • 6.2 Data Analysis Techniques for IDS

    • 6.3 Network Monitoring Tools and Best Practices

    • 6.4 Detecting and Responding to Security Incidents

  • Chapter 7: Identifying and Mitigating Attacks Using Data

    • 7.1 Common Types of Attacks (DDoS, Phishing, Man-in-the-Middle, etc.)

    • 7.2 Data-Driven Approaches to Attack Detection

    • 7.3 Leveraging Threat Intelligence and Data Analysis for Attack Mitigation

    • 7.4 Case Study: Detecting and Preventing a Real-World Attack

Part IV: Advanced Topics in Network Security Data Analysis

  • Chapter 8: Machine Learning and AI for Network Security

    • 8.1 Introduction to Machine Learning in Cybersecurity

    • 8.2 Supervised vs. Unsupervised Learning for Threat Detection

    • 8.3 Training Machine Learning Models for Security Applications

    • 8.4 AI-Driven Threat Intelligence Systems

    • 8.5 The Role of Deep Learning in Advanced Threat Detection

  • Chapter 9: Behavioral Analytics for Network Security

    • 9.1 The Concept of User and Entity Behavior Analytics (UEBA)

    • 9.2 Detecting Insider Threats Through Behavioral Analysis

    • 9.3 Establishing Baselines for Normal Network Behavior

    • 9.4 Responding to Anomalies in User Behavior

    • 9.5 Integrating UEBA into Situational Awareness Systems

Part V: Operationalizing Situational Awareness in Network Security

  • Chapter 10: Building an Effective Security Operations Center (SOC)

    • 10.1 The Role of the SOC in Network Security

    • 10.2 Key Functions and Responsibilities of the SOC

    • 10.3 Integrating Situational Awareness into SOC Operations

    • 10.4 Tools and Technologies for SOC Effectiveness

  • Chapter 11: Incident Response and Decision Making

    • 11.1 Incident Response Lifecycle

    • 11.2 Leveraging Situational Awareness in Decision Making

    • 11.3 Coordinating with Other Teams for Incident Response

    • 11.4 Case Study: Real-time Response to a Security Incident

Part VI: Challenges and Future Directions

  • Chapter 12: Challenges in Network Security Data Analysis

    • 12.1 Data Overload and False Positives

    • 12.2 Privacy and Ethical Considerations

    • 12.3 Ensuring Data Quality and Integrity

    • 12.4 The Human Element in Situational Awareness

  • Chapter 13: The Future of Network Security and Situational Awareness

    • 13.1 Emerging Trends in Network Security Data Analysis

    • 13.2 Future Technologies in Threat Detection

    • 13.3 The Evolution of Artificial Intelligence in Security

    • 13.4 Recommendations for Enhancing Situational Awareness in the Future

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Tags: Michael Collins, Network Security, Situational Awareness