DOJO Details
There is ONE offering of this 2-Day dojo.
March 18 - 19 (Saturday to Sunday), 2024
Attendance available as
In-Person Training
On-Line Training
Course Pre-requisites
Basic scripting (bash or python)
Basic familiarity with AI
At least a mid-level cybersecurity or technology professional
Course Learning Objectives
Understand the fundamental concepts of AI and their relevance in cybersecurity.
Identify and explore various AI tools and techniques used in threat detection and response.
Analyze real-world applications of AI in cybersecurity through case studies.
Gain practical experience by applying AI techniques in simulated cybersecurity scenarios.
Develop strategies for integrating AI into existing cybersecurity frameworks.
Who Should Attend
Cybersecurity professionals who are looking to secure AI applications or those looking to integrate AI solutions into cybersecurity work.
Course Agenda
Day 1: Understanding AI in Cybersecurity
Morning Session: Introduction to AI in Cybersecurity
Learning Objective: Gain a foundational understanding of AI concepts and how they apply to cybersecurity.
Topics: Basics of AI, Machine Learning, and Deep Learning; Overview of AI in cybersecurity; AI's role in threat detection and response.
Afternoon Session: AI Tools and Techniques for Cybersecurity
Learning Objective: Explore various AI tools and techniques relevant to cybersecurity.
Topics: AI-based threat intelligence, Anomaly detection using machine learning, AI in phishing detection, AI for network security.
Day 2: Implementing AI in Cybersecurity Practice
Morning Session: Case Studies and Real-World Applications
Learning Objective: Analyze real-world case studies where AI has been successfully implemented in cybersecurity.
Topics: Case studies of AI in preventing data breaches, AI in fraud detection, AI in incident response.
Afternoon Session: Workshop and Hands-On Training
Learning Objective: Apply learned AI techniques in simulated cybersecurity scenarios.
Activities: Hands-on exercises with AI tools, Simulated scenarios for AI integration in cybersecurity, Group discussion and feedback.
Hardware Requirements
A notebook capable of running python and 16 GB of RAM
Software Requirements
SSH client able to access provided AWS images
Python3 installed on laptop able to run Jupyter notebooks
Included Course Materials
Course materials in PDFs
All required additional files: source code, documentation, installation binaries
About the Instructor: John Bambenek
John Bambenek is President of Bambenek Labs and a handler with the SANS Internet Storm Centre. He has over 20 years experience in Information Security and leads several International investigative efforts tracking cybercriminals - some of which have lead to high profile arrests and legal action. He currently tracks neonazi fundraising via cryptocurrency and publishes that online to twitter and has other monitoring solutions for cryptocurrency activity. He specializes in disruptive activities designed to greatly diminish the effectiveness of online criminal operations. He has produced some of the largest bodies of open-source intelligence, used by thousands of entities across the world.