{"id":32394524,"url":"https://github.com/clandolt/mlcysec_notebooks","last_synced_at":"2026-07-09T04:32:07.542Z","repository":{"id":320161672,"uuid":"1072326632","full_name":"clandolt/mlcysec_notebooks","owner":"clandolt","description":"Repository of Jupyter notebook tutorials for teaching the Machine Learning in Cybersecurity Course at the Saarland University, WiSe 2025/26","archived":false,"fork":false,"pushed_at":"2026-01-12T14:17:28.000Z","size":35046,"stargazers_count":8,"open_issues_count":0,"forks_count":1,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-01-12T20:55:50.261Z","etag":null,"topics":["anomaly-detection","cybersecurity","deep-learning","gan","intrusion-detection","machine-learning"],"latest_commit_sha":null,"homepage":"https://christophlandolt.com/mlcysec_notebooks/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/clandolt.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-10-08T15:07:53.000Z","updated_at":"2026-01-12T14:13:28.000Z","dependencies_parsed_at":"2025-10-30T15:05:32.496Z","dependency_job_id":null,"html_url":"https://github.com/clandolt/mlcysec_notebooks","commit_stats":null,"previous_names":["clandolt/mlcysec_notebooks"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/clandolt/mlcysec_notebooks","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clandolt%2Fmlcysec_notebooks","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clandolt%2Fmlcysec_notebooks/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clandolt%2Fmlcysec_notebooks/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clandolt%2Fmlcysec_notebooks/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/clandolt","download_url":"https://codeload.github.com/clandolt/mlcysec_notebooks/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clandolt%2Fmlcysec_notebooks/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":35287396,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-07-09T02:00:07.329Z","response_time":57,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["anomaly-detection","cybersecurity","deep-learning","gan","intrusion-detection","machine-learning"],"created_at":"2025-10-25T05:58:54.219Z","updated_at":"2026-07-09T04:32:07.537Z","avatar_url":"https://github.com/clandolt.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"CISPA Machine Learning in Cybersecurity \n======================================= \n\nRepository of Jupyter notebook tutorials for teaching the Machine Learning in Cybersecurity Course at the Saarland University, WiSe 2025/26\n\n\u003e **Note:** You can browse the rendered notebooks directly in your browser via the [course website](https://cms.cispa.saarland/mlcysec_ws25/).\n\n---\n\n## 📘 Course Information\n\n**Course website:** [https://cms.cispa.saarland/mlcysec_ws25/](https://cms.cispa.saarland/mlcysec_ws25/)\u003cbr\u003e\n**Course edition:** Winter term 2025/2026 (Oct 13 – Feb 06)\u003cbr\u003e\n**Recordings:** Will follow\u003cbr\u003e\n**Instructor:** Christoph R. Landolt\n\n---\n\n## ⚙️ How to Run the Notebooks\n\nThe website hosts HTML-exported versions of the notebooks for convenient reading on any device.  \nHowever, we encourage you to run them yourself to gain hands-on experience.  \nYou can do this in three main ways:\n\n### 🖥️ Run Locally (CPU)\nAll notebooks are available in this GitHub repository.  \nYou can also find them here:  \n👉 [https://github.com/clandolt/mlcysec_notebooks](https://github.com/clandolt/mlcysec_notebooks)\n\n- Designed to run on standard laptops (no GPU required).\n\n### ☁️ Google Colab\nPrefer to use a hosted environment or want GPU support? Use [Google Colab](https://colab.research.google.com/notebooks/intro.ipynb#recent=true).\n\n- Each notebook includes a “Run in Colab” badge on the documentation website.\n- Enable GPU support via: `Runtime → Change runtime type → GPU`.\n\n---\n\n## 🧭 Tutorial Lessons\n\nThe **Exercise Schedule** (below) lists the practical/tutorial sessions associated with the course tutorials.\n\n| Date | Time | Topic |\n|------|------|-------|\n| **29.10.2025** | 16:15–17:45 | Tutorial: ML Basics / Setup |\n| **05.11.2025** | 16:15–17:45 | Q\u0026A: ML Basics |\n| **12.11.2025** | 16:15–17:45 | Introduction Ex1: Train ML IDS |\n| **03.12.2025 (online)** | 16:15–17:45 | Ex1 Review: Train ML IDS |\n| **10.12.2025** | 16:15–17:45 | Introduction Ex2: Evade ML IDS |\n| **07.01.2026** | 16:15–17:45 | Ex2 Review: Evade ML IDS |\n| **14.01.2026** | 16:15–17:45 | Introduction Ex3: AI for CTF |\n| **04.02.2026** | 16:15–17:45 | Ex3 Review: AI for CTF |\n\n---\n\n## 💬 Feedback, Questions, or Contributions\n\nThis is the first edition of the **Machine Learning in Cybersecurity** tutorials.  \nWe appreciate all feedback — whether it’s a typo, a bug, or a suggestion for improvement.\n\nIf you discover a **mistake or issue in a notebook**, please [open a GitHub issue](../../issues) so we can track and resolve it publicly.\n\nYou can also reach out directly via email (`christoph dot landolt at cispa dot de`), or speak to us during a exercise session.\n\nIf you find the tutorials helpful, please cite this course as:\n\n```bibtex\n@misc{landolt2025_mlcysec,\n  title        = {CISPA Machine Learning in Cybersecurity},\n  author       = {Christoph R. Landolt and Mario Fritz},\n  year         = {2025},\n  howpublished = {\\url{https://christophlandolt.com/mlcysec_notebooks/}},\n}\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fclandolt%2Fmlcysec_notebooks","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fclandolt%2Fmlcysec_notebooks","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fclandolt%2Fmlcysec_notebooks/lists"}