Artificial intelligence (AI) is an increasingly used component within our #cybersecurity arsenal, to defend, detect, and automate incident response. Equip yourself to critically evaluate the underpinnings of next generation #AI powered cybersecurity tools by understanding key machine learning (ML) algorithms, training methodologies, development options, and #machinelearning examples for attacker behaviour detection. Cut through the hyperbole and empower yourself to ask insightful and probing questions that validate or expose vendor claims around AI cybersecurity solutions.
💡Learning Outcomes: ► Understand the principle operations and security applications of key ML algorithms ► Learn how to select appropriate ML algorithm training approaches ► Examine a security threat detection and ML algorithms development lifecycle ► Evaluate make vs buy decisions for ML in cybersecurity ► Learn probing questions on AI and ML that will draw out insight or demonstrate weaknesses from ► vendors of AI security solution
00:00 Building Security That Thinks: Machine Learning for Cybersecurity Professionals 00:15 What is AI? What is Machine Learning? 02:14 What are the 3 types of Machine Learning? 03:25 What is supervised Machine Learning? 05:35 What is unsupervised Machine Learning? 06:48 What is Deep Learning? 08:24 What is the difference between traditional Machine Learning and Deep Learning? 11:10 How to use Machine Learning as a Cybersecurity asset 18:51 What does it take to build an algorithm? 20:15 What are the five questions to ask a cybersecurity AI vendor? 21:20 Five key takeaways 22:40 Q&A
