In the era of advanced information technology, data has become one of the most valuable assets that organizations rely on to enhance their security strategies and make informed decisions. Among the most critical data types is cyber data, which pertains to cybersecurity threats and cyberattacks. The ability to analyze this data is crucial for cybersecurity teams in detecting and mitigating threats and attacks.

The British Academy for Training and Development offers a specialized training course in Cyber Data Analysis According to US Standards. This course is designed to equip participants with the knowledge and skills needed to analyze cyber data using the latest tools and techniques based on US standards, focusing on the policies and practices that are foundational to cyber data analysis and protection.

The course covers various aspects of cyber data analysis, starting from data collection to its processing and analysis to detect cybersecurity threats and anomalies. The course also addresses the best practices for handling cyber data within the US context, making it ideal for professionals in this field.

Who Should Attend?

• Cybersecurity Analysts who need to develop their skills in analyzing threat-related cyber data.
• IT Specialists and System Administrators who handle cyber data and want to understand the advanced tools and techniques used in its analysis.
• Cybersecurity Managers who aim to apply US standards in their teams and analyze data related to cybersecurity threats.
• Compliance Officers in organizations who need to understand how to analyze cyber data in accordance with legal and regulatory frameworks.
• Cybersecurity Consultants who advise businesses and organizations on how to manage and protect cyber data.

Knowledge and Benefits:

After completing the program, participants will be able to master the following:

• Understand the basics of cyber data and how to collect and analyze it according to US standards.
• Apply modern tools and techniques to detect cyber threats through data analysis.
• Analyze cyber data to extract patterns and trends indicative of suspicious activity.
• Utilize advanced data analysis tools such as statistical analysis, machine learning, and network analysis to identify abnormal patterns.
• Interact with cyber data and transform it into actionable insights to improve threat detection capabilities.
• Adhere to US standards for analyzing cyber data, including NIST and ISO 27001, and apply them in various operational environments.

• What is Cyber Data?
  • Definition of cyber data and its role in cybersecurity.
  • Importance of analyzing cyber data in the context of security.
  • Differences between traditional data and cyber data.
• Basic Tools for Cyber Data Analysis
  • Tools and techniques used for collecting cyber data.
  • Analyzing cyber data in corporate environments.
  • Role of security information management systems in cyber data collection.
• Introduction to US Standards for Data Security
  • Understanding US standards such as NIST and FISMA.
  • How to apply US security standards in the collection and analysis of cyber data.
  • The role of standards in safeguarding cyber data and ensuring rapid response.

• Sources of Cyber Data
  • Types of cyber data: network traffic, logs, attacks, and analytics.
  • Internal and external sources of cyber data in organizations.
  • How to handle and process collected data for analysis.
• Techniques for Data Collection
  • Using data collection tools such as network traffic monitoring, log systems.
  • Network scanning techniques and gathering critical information.
  • How to handle collected data and convert it into a format for analysis.
• Techniques for Cyber Data Analysis
  • Traditional methods for data analysis: statistical analysis, data classification.
  • Using advanced software for data analysis: Python, R.
  • Predictive methods for identifying patterns and potential attacks.

• Network Traffic Analysis
  • Using tools to analyze network traffic and detect abnormal activities.
  • Recognizing tools like Wireshark and NetFlow for traffic analysis.
  • Importance of continuous traffic monitoring in organizational environments.
• Machine Learning for Data Analysis
  • How machine learning helps in detecting threats faster.
  • Applications of artificial intelligence for detecting patterns.
  • Using neural networks in cyber data analysis.
• Network Analysis Tools
  • Understanding network analysis for detecting intrusions.
  • Specialized tools like Splunk and ELK Stack for data analysis.
  • Techniques for real-time analysis of network data.

• Detecting Patterns and Threats
  • Recognizing normal and abnormal patterns in cyber data.
  • Methods for detecting cybersecurity threats using data analysis.
  • Identifying advanced threats that might target organizations.
• Rapid Response to Threats
  • How to use available data for quick response to cyberattacks.
  • Analyzing cyber data to assess the scope of damage.
  • Strategies for building effective responses using data analysis.
• Threat Indicators and Interaction with Security Teams
  • How data can provide threat indicators for security teams.
  • Tools and techniques for sharing threat indicators.
  • Collaboration between different teams for quick threat analysis.

• Compliance with US Standards in Data Analysis
  • Challenges and opportunities in applying US standards.
  • Alignment with NIST and ISO 27001 in cyber data analysis.
  • How to implement standards in cybersecurity programs.
• Cyber Data Reporting and Management
  • How to prepare reports that meet regulatory requirements.
  • Strategies for data retention and security policies.
  • Handling sensitive data and securing it.
• Analyzing Future Threats
  • Future technologies in cyber data analysis.
  • Role of AI and machine learning in future threat detection.
  • Predicting evolving threats using data analysis.

• Artificial Intelligence and Machine Learning
  • How AI is used to enhance anomaly detection in cyber data.
  • Data analysis through predictive algorithms.
  • Advantages and challenges of AI in cybersecurity.
• Evolving Cybersecurity Frameworks
  • Evolution of cybersecurity standards in the US and globally.
  • How US standards integrate with global cybersecurity trends.
  • Compliance with data protection laws like CCPA and GDPR.
• Continuous Analysis and Adapting to New Threats
  • Ongoing analysis of data to identify new and emerging threats.
  • Building adaptive systems for analyzing advanced cyber threats.
  • Future trends in cybersecurity and how to handle them using data.