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Cybersecurity Data Science
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Introduction
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Machine Learning and Malware Detection
- Setting Up Your Lab Environment
- Obtaining a Malware Dataset
- Obtaining a Benign Dataset
- Malware Analysis 101
- PE File: Introduction
- Installing the pefile Library
- Extracting PE Information Using pefile
- TF-IDF
- Creating a Train-Test Split
- Training a Classifier
- Tackling Class Imbalance
- Handling Type I and Type II Errors
- N-Grams
- Hash-Grams
- Building an N-Gram Classifier
- MalConv: Deep Learning on Executables
- Section 1 – Conclusion
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Machine Learning and Intrusion Detection
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Machine Learning and Offensive Security
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Machine Learning for Red Team Hackers
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Introduction
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Hacking CAPTCHA Systems
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Smart Fuzzing
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Evading Machine Learning Malware Classifiers
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Adversarial Machine Learning
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DeepFake
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Hacking Machine Learning
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Machine Learning for Cybersecurity Cookbook
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Cybersecurity Data Science Newsletter Archive
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