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Il y a 5 modules dans ce cours
The course "Machine Learning and Emerging Technologies in Cybersecurity" offers an in-depth exploration of machine learning applications in cybersecurity, focusing on techniques for threat detection and prevention. Participants will gain a solid grounding in machine learning fundamentals, including neural networks, clustering, and support vector machines, tailored specifically for cybersecurity contexts. Unique to this course is the integration of machine learning with Intrusion Detection Systems (IDS), equipping learners with practical skills to enhance threat detection capabilities.
Additionally, the course examines Tor networking, providing insights into secure and anonymous communication systems, as well as the critical role of IDS within Cyber Security Incident Response Teams (CSIRTs) in enterprise environments. By the end of the course, learners will not only understand how to apply advanced machine learning techniques but also be proficient in tools like RapidMiner and Security Onion. This blend of theory and hands-on application ensures that participants leave with the skills needed to tackle real-world cybersecurity challenges effectively, making this course a vital resource for those looking to advance their careers in cybersecurity and data science.
This course provides a comprehensive introduction to machine learning and data mining, covering key algorithms and tools like RapidMiner and Security Onion. Students will explore advanced topics such as neural networks, clustering, and support vector machines, while also learning to evaluate model performance through confusion matrices and ROC curves. Additionally, the course delves into ToR architecture, privacy concerns, and the practical installation of ToR clients. Emphasis will be placed on incident response within Computer Security Incident Response Teams (CSIRTs) and effective information-sharing practices. By the end of the course, participants will have a robust understanding of both machine learning techniques and their applications in cybersecurity.
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1 vidéo3 lectures
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The course delves deeper into specific approaches, including neural networks, clustering, and support vector machines (SVMs), providing students with a solid foundation in both the theory and practice of these advanced techniques.
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5 vidéos3 lectures3 devoirs2 laboratoires non notés3 plugins
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5 vidéos•Total 68 minutes
Introduction•2 minutes
Introduction to Machine Learning Concepts •20 minutes
Neural Networks•16 minutes
Clustering•14 minutes
Help Vector Machines•16 minutes
3 lectures•Total 220 minutes
Reading References•90 minutes
Reading References•90 minutes
Self-Reflective Reading: AI, Ethics, and Military Collaboration•40 minutes
3 devoirs•Total 90 minutes
Machine Learning I•60 minutes
Introduction to Machine Learning and Data Mining•15 minutes
Implementing and Evaluating IBM Watson for Fraud Detection•15 minutes
2 laboratoires non notés•Total 120 minutes
Practice Lab: Building and Training a Neural Network with Keras•60 minutes
Practice lab: Implementing and Tuning a Perceptron in Python•60 minutes
3 plugins•Total 43 minutes
Assurance for Machine Learning Video•15 minutes
RapidMiner Example•15 minutes
Deep Learning Using Keras – Training Neural Network•13 minutes
Machine Learning II
Module 3•9 heures à terminer
Détails du module
This course explores the integration of Machine Learning (ML) algorithms into Intrusion Detection Systems (IDS) to enhance threat detection capabilities.
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3 vidéos4 lectures3 devoirs5 plugins
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3 vidéos•Total 27 minutes
Introduction•3 minutes
Choosing an ML Algorithm•5 minutes
Applying ML to ID•20 minutes
4 lectures•Total 360 minutes
Reading References•120 minutes
Reading References•120 minutes
Self-Reflective Reading: Exploring Machine Learning in Intrusion Detection Systems•60 minutes
Self-Reflective Reading: Analyzing Netflow Data and Machine Learning Models in Cybersecurity•60 minutes
3 devoirs•Total 90 minutes
Types of Machine Learning Algorithms and their Application in IDS•15 minutes
Challenges in Implementing ML in IDS and Evaluation Techniques•15 minutes
Machine Learning II•60 minutes
5 plugins•Total 63 minutes
Enigma Talk by Jeremy Howard on Deep Learning (Optional)•20 minutes
Data Preparation•9 minutes
Applying the Model•7 minutes
Building the Model•19 minutes
Validating a Model•8 minutes
ToR Networking
Module 4•9 heures à terminer
Détails du module
This course provides a comprehensive understanding of The Onion Router (ToR) architectures, focusing on the critical components that make up this secure and anonymous communication system.
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5 lectures3 devoirs2 plugins
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5 lectures•Total 410 minutes
Reading References•120 minutes
Reading References•120 minutes
ToR History & Data Anonymization•90 minutes
Self-Reflective Reading: Exploring Neural Networks and Intrusion Detection in ToR Networks•40 minutes
Self-Reflective Reading: Understanding Tor Network Anonymity and Security•40 minutes
3 devoirs•Total 90 minutes
ToR Networking•60 minutes
Introduction to ToR Architectures and Node Types•15 minutes
ToR Relays, Security Concerns, and Data Anonymization•15 minutes
2 plugins•Total 37 minutes
ToR Networking Video•35 minutes
DJ Ware - Discussion of "The Onion Router" ToR•2 minutes
IDS in Context
Module 5•12 heures à terminer
Détails du module
This module explores the critical role of Intrusion Detection Systems (IDS) within Cyber Security Incident Response Teams (CSIRTs), particularly in high-volume enterprise environments.
Inclus
7 vidéos7 lectures4 devoirs4 plugins
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7 vidéos•Total 127 minutes
Introduction•4 minutes
Forming a CSIRT•23 minutes
IDS Response Process•28 minutes
Information Sharing•20 minutes
Future Applications of IDS/IPS•14 minutes
Technical Challenges Yet to Be Resolved•23 minutes
Where to Get Information on the Future of IDS/IPS?•16 minutes
7 lectures•Total 300 minutes
Reading References•60 minutes
Concrete Steps for Implementing an Information Security Program•20 minutes
Crisis Communications During a Security Incident•20 minutes
Reading References•60 minutes
Reading References•60 minutes
Self-Reflective Reading: Analyzing the Cyber Intelligence Sharing and Protection Act (CISPA)•40 minutes
Self-Reflective Reading: Integrating IDS and CSIRT in Cybersecurity and Evaluating CISA•40 minutes
4 devoirs•Total 105 minutes
IDS in Context•60 minutes
Forming and Managing a CSIRT•15 minutes
Executing IDS Response Processes with Security Onion•15 minutes
Emerging Trends and Future Challenges in Intrusion Detection and Prevention Systems (IDS/IPS)•15 minutes
4 plugins•Total 176 minutes
Learning Rules for Anomaly Detection •60 minutes
The New Fundamentals of Security - Mike Fey - RSA Conference US 2013 Keynote•28 minutes
Big Data Redefines Security - Arthur Coviello, Jr. - RSA Conference US 2013 Keynote (14E)•31 minutes
Tech Talk on How to Detect Intruders Already in Your System •57 minutes
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