There is a total of seven self-contained modules that are provided by this project, with each module targeting a
specific concept or technique used in cyber security or machine learning. Unless otherwise stated in the lab
documentation, there is no required order of completion. However, completing some labs before others may be
beneficial.
Module code is available both through a GitHub repository and a Docker container. Docker containers are built automatically whenever a change is posted to the corresponding GitHub repository, meaning both are always kept in parity. If you opt to use the pre-built Docker images, it is still advised to read the README file on GitHub for any precautions that need to be taken during the lab. Links for both can be found below.
Lab documents, slides, and explanation video(s) for students is found in the download. It is recommended for students to review these materials thoroughly before beginning the lab exercises.
Instructors, please reach out for access to the additional instructor materials.
| # | Concepts | GitHub Repository | Docker Hub Container | Download Lab Document, Slides, and Video |
|---|---|---|---|---|
| 1 | Malware data collection, feature extraction and mapping | AIMA-Project/AAMA-Lab01 | abcyslab/aama_lab01 | module1.zip |
| 2 | Malware Detection and Classification | AIMA-Project/AAMA-Lab02 | abcyslab/aama_lab02 | module2.zip |
| 3 | White-box evasion attack | AIMA-Project/AAMA-Lab03 | abcyslab/aama_lab03 | module3.zip |
| 4 | Black-box evasion attack | AIMA-Project/AAMA-Lab04 | abcyslab/aama_lab04 | module4.zip |
| 5 | Dataset Poisoning Attack | AIMA-Project/AAMA-Lab05 | abcyslab/aama_lab05 | module5.zip |
| 6 | Dataset Poisoning Defense | AIMA-Project/AAMA-Lab06 | pmummaneni/aama_lab06 | module6.zip |
| 7 | Adversarial Training | AIMA-Project/AAMA-Lab07 | pmummaneni/aama_lab07 | module7.zip |