Aprendizagem Aplicada à Segurança (2023)

Theoretical material

The theorical material can be found here.

Explore the examples

Follow the instructions bellow:

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

The notebooks can be found here

Schedule

Date	Class	Topic
15/09/2023	1	Introduction
22/09/2023	2	SPAM Detector
29/09/2023	3
06/10/2023	4
13/10/2023	5	Anomaly Detection
20/10/2023	6
27/10/2023	7
03/11/2023	8	Mid-term Exam
10/11/2023	9	Malware Analysis
17/11/2023	10
24/11/2023	11
01/12/2023	12	Project
08/12/2023	13
15/12/2023	14
22/12/2023	15

Bibliography

• S. Halder and S. Ozdemir, Hands-On Machine Learning for Cybersecurity: Safeguard your system by making your machines intelligent using the Python ecosystem. Packt Publishing Ltd, 2018.
• C. Chio and D. Freeman, Machine Learning and Security. O’Reilly, 2018.
• A. Parisi, Hands-On Artificial Intelligence for Cybersecurity: Implement smart AI systems for preventing cyber attacks and detecting threats and network anomalies. Packt Publishing Ltd, 2019.
• E. Tsukerman, Machine Learning for Cybersecurity Cookbook. Packt Publishing Ltd, 2019.
• J. P. Mueller and R. Stephens, Machine Learning Security Principles. Packt Publishing Ltd, 2019.

Authors

• Mário Antunes - mariolpantunes

License

This project is licensed under the MIT License - see the LICENSE file for details