Latest Student Testimonial:
With experience in the Department of Defense, I found this training essential for industry professionals. It provides an enhanced perspective on intelligence analysis, covering and applying state-of-the-art concepts to real-world scenarios. This comprehensive training promotes a solid understanding of intelligence tradecrafts, and I strongly recommend it to those new or experienced in the cyber intelligence field.
Course Overview (high-level AI list below):
Anonymity and Passive Persona Setup:
- Glossary and Taxonomy
- Operational Security (OPSEC)
Understanding Intelligence:
- What It Can and Cannot Do
- Open-Source Intelligence Techniques and Tools
- Adversary Targeting, Collection Methods, and Techniques
- Types of Evidence and Confidence Levels
- Analysis Methods and Writing Techniques
- AI Infused collection, analysis, and analytic writing methods.
- Supercharge Your Data Collection:
Examine AI-powered solutions automatically sift through online data zeroing in on the information that matters most. Now, identify emerging threats or trends faster and more accurately than ever, thanks to advanced Natural Language Processing (NLP) algorithms.
Unlock Next-Level Analysis:
Traditional analysis methods are no match for the speed and accuracy of AI-enhanced systems. Real-time algorithms sift through enormous datasets, spot complex patterns, and identify network anomalies instantaneously. Imagine predicting tomorrow's cybersecurity threats today—that is the power of AI in cyber intelligence analysis.
Elevate Your Analytic Writing:
Why struggle with complex reports when AI can do the heavy lifting? NLP-enabled writing tools help you create reports that are both rich in insight and easy to digest. From auto-generating data summaries to suggesting content structure, we make analytic writing a breeze.
Achieve the Unthinkable with AI Synergy:
Integrating AI into your cyber intelligence operations does not just make you faster—it makes you smarter. Harness the combined power of human expertise and machine intelligence for more actionable insights, delivered more efficiently and accurately.
Are you ready for intelligence that is not just smart, but AI-smart? Upgrade your cyber intelligence capabilities and navigate through the complex and risky world of modern cybersecurity like a pro.
Instructor Testimonials:
- "The Cyber Intelligence Training adds rapid returns to Cyber Intel Analysts and your Security Operations."
- "Fantastic class that gets to the foundational aspects of traditional tradecraft."
- "One of the best Cyber Threat Intelligence training courses I've attended."
- "This course was excellent; I have already recommended it to my former colleagues."
AI-Enhanced Training for Cybersecurity and Intelligence
This comprehensive training program adopts a multi-faceted approach to cybersecurity and intelligence analysis, harnessing the power of artificial intelligence (AI) to enhance traditional methodologies. From darknet exploration to social media analysis, the course equips participants with the skills and tools to navigate today's complex cyber landscape.
Software and Tools Integration
Participants will explore essential darknet areas while learning to navigate them safely, and AI algorithms will scrape and analyze darknet data for threat identification. AI will also play a role in social media analysis through natural language processing (NLP) for sentiment and trend recognition. The course employs Maltego, a graph-based link analysis tool, for entity mapping while also integrating AI for automated entity recognition. Tools like Open Semantic Search, Oracle Virtual Box, and Tracelabs provide a basis for comprehensive intelligence gathering. Here, too, AI algorithms improve semantic searches and data indexing.
Real-World Exposure
Live case studies allow for the application of learned methods and techniques. AI tools augment these studies with predictive analysis, data correlation, and cyber threat hunting. Supporting materials, including two books and over fifty documents, come with AI-generated summaries and visualizations.
Course Benefits and Audience
The course standardizes language across the intelligence community, offering expertise in AI-assisted techniques like automated data scraping and sentiment analysis. Designed for intelligence analysts, cyber risk professionals, and researchers, the course is particularly beneficial for those interested in AI applications in cybersecurity.
Requirements and Certification
Participants should be familiar with Internet browsers, Office 365, and general intelligence concepts. A laptop with 8GB RAM and a GPU suitable for machine learning tasks is also necessary. Completing the course certifies students as Cyber Intelligence Tradecraft Professionals and offers 52 Continuing Professional Education credits.
Unique Features
What sets this course apart is its in-depth coverage of the intelligence lifecycle, hands-on assignments, and AI-enhanced exercises. It also includes written and oral case study presentations enriched by AI-generated visualizations. Treadstone 71's course restricts resale or commercial use of its materials, including AI resources.
High-Level AI Outline
The course incorporates AI in various facets. For example, AI tools will assess and optimize operational security (OPSEC), identify early indicators of change using STEMPLES Plus and Hofstede Principles, and assist in data aggregation and correlation during adversary targeting. Automated features within Hunch.ly and open-source tools like Tracelabs are also integrated for semantic analysis and optimization.
By incorporating AI at multiple stages, the course aims to produce professionals who are versed in traditional intelligence work and highly proficient in leveraging AI for enhanced efficiency and effectiveness.
- Involves real-world experience from the headlines, using all methods and techniques referenced in the course material.
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AI Integration: Analyze real-world case studies that involve AI tools for predictive analysis, data correlation, and cyber threat hunting.
Materials Provided:
- Two books and over 50 course documents, including AI-generated summaries and data visualizations, will aid your understanding.
Course Benefits:
- Use of recognized language across the intelligence community.
- Understanding what intelligence is and isn't.
- Skill in using multiple analytic tools, methods, and techniques.
- Develop expertise in AI-assisted analysis techniques, such as automated data scraping, sentiment analysis, and predictive modeling.
- Knowledge of how to evaluate and synthesize data.
- Learn to apply machine learning algorithms for data evaluation and pattern recognition.
- Ability to recognize and mitigate cognitive biases.
- Use AI-powered tools to identify and mitigate biases in intelligence data and analysis.
- Understanding of denial and deception techniques.
- Employ AI to uncover stealthy tactics and hidden data within multi-layered deception techniques.
Target Audience:
- Intelligence analysts, researchers, cyber risk management professionals, incident response leadership, students, and investigators non-inclusively.
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AI Integration: Particularly beneficial for professionals and students interested in AI applications in cybersecurity and intelligence analysis.
Requirements:
- Familiarity with Internet browsers, Office 365, and general intelligence concepts.
- Laptop with administrative access, 8GB RAM, 100GB free hard drive space.
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AI Integration: An additional requirement for a GPU suitable for machine learning tasks and AI software installations.
Certification:
- Students who complete the course will be certified as Cyber Intelligence Tradecraft Professionals, receiving 52 CPEs, inclusive of AI applications in cyber intelligence.
How This Course Differs:
- In-depth sections along the intelligence lifecycle.
- Hands-on assignments and demonstrations.
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AI Integration: Additional hands-on exercises involving AI-based tools and algorithms for various intelligence tasks.
- Written and oral presentations of case studies.
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AI Integration: Learn to incorporate AI-generated visualizations and summaries in your presentations for more compelling narratives.
Course Fee:
- Includes books, templates, structured techniques applications, AI software resources, and more.
Additional Notes:
- This course is highly specialized, focusing on intelligence community tradecraft.
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AI Integration: Expanded to cover AI technologies that are increasingly prevalent in modern intelligence operations.
- Offered by Treadstone 71, it lays the foundation for a solid program.
- Resale or commercial use of the course material, including AI resources, is restricted.
Learn to fish for yourself in the complex cyber intelligence world with practical examples, immediate usability, and cutting-edge AI techniques.
High Level AI Outline
Anonymity and Passive Persona Setup:
- Use human directed and AI-infused collaboration to detect potential risks and vulnerabilities during the persona setup process.
Glossary and Taxonomy:
- Implement an AI-powered search function to allow students to find terminology definitions and relationships between terms quickly.
Operational Security - OPSEC:
- Introduce AI tools that can assess and optimize your OPSEC setup, identifying any potential weak links in the security chain.
What Intelligence Can and Cannot Do:
- Provide real-time simulations with AI to demonstrate the limits and capabilities of modern intelligence methods.
Open-Source Intelligence Techniques and Tools:
- Learn how to use AI for scraping, sentiment analysis, and data categorization within open-source Intelligence.
Stakeholder Analysis:
- Use AI to automate stakeholder sentiment analysis based on public statements or social media activity.
Intelligence Requirements to PIRs:
- Implement AI to prioritize PIRs based on historical data and forecasting.
STEMPLES Plus - Hofstede Principles - Indicators of Change:
- Use AI for pattern, trend, and tendency analysis and forecasting to identify early indicators of change across various cultural and social dimensions. Targeted STEMPLES Plus AI analysis.
Adversary Targeting - D3A F3EAD:
- Integrate AI to assist in data aggregation and correlation during the Decide, Detect, Deliver, and Assess phases of adversary targeting, while assisting with targeting.
Collection Methods and Techniques:
- Using AI to sort and categorize collected data automatically improves efficiency and focus.
Collection Planning, IRs/PIRs/EEIs/Indicators/SIRs:
- AI Integration: Employ AI to optimize the planning phase, allocating resources more effectively based on predictive analytics.
Collection Process Flow:
- AI Integration: Integrate AI tools to automate certain stages of the collection process, allowing for more streamlined and effective data gathering.
Collection (OSINT) Tools and Targeting:
- AI Integration: Use AI algorithms to identify patterns and suggest potential OSINT sources that might be overlooked.
Most Likely Threat Actors:
- AI Integration: Use machine learning algorithms to continually update and prioritize threat actor profiles based on emerging data and trends.
Hunch.ly:
- Introduce automated analysis features within Hunch.ly, using AI to highlight relevant data and trends.
Open Semantic Search - Oracle Virtual Box - OVA Setup - Tracelabs:
- AI Integration: Implement AI algorithms for semantic analysis and optimize virtual machine settings for different tasks.
Darknet Sites of Interest:
- AI Integration: Explore AI tools that scrape and analyze darknet data for threat intelligence.
Social Media - Off the Beaten Path:
- AI Integration: Employ AI to find and analyze data from less common social media platforms.
Burn Phone Setup and Use (US Only):
Intelligence Lifecycle Production Methods:
- AI Integration: Introduce AI automation at various stages of the intelligence lifecycle to improve efficiency and accuracy.
Structured Analytic Techniques:
- Use AI to validate or automatically generate alternative hypotheses based on available data.
Adversary Denial and Deception:
- Use AI to model adversary denial and deception techniques for better counterstrategies.
Source Credibility and Relevance:
- Implement automated credibility and relevance scoring through machine learning algorithms.
Confidence Levels:
- Employ AI to calculate confidence levels based on various data inputs and historical reliability metrics.
Analytic Writing, BLUF, AIMS:
- Utilize AI-based grammar and style checkers to refine and improve analytical writing.
Forecasting in Your Writing:
- Use AI-driven estimative analytics tools to enhance forecasting accuracy in analytic reports.
Threat Hunting with TaHiTI & MaGMa:
- Integrate AI to automatically identify patterns, anomalies, and potential threats during threat-hunting.
By enhancing the course with AI at multiple touchpoints, students will gain practical experience utilizing AI for intelligence work, thereby becoming more effective and efficient professionals in the field.