{"id":16765076,"url":"https://github.com/trykatchup/ml-iot-malware-analysis","last_synced_at":"2025-04-10T18:22:14.636Z","repository":{"id":73339108,"uuid":"585154059","full_name":"TryKatChup/ML-IOT-malware-analysis","owner":"TryKatChup","description":"Machine Learning models for IoT traffic malware detection. (Cybersecurity - Alma Mater Studiorum - University of Bologna)","archived":false,"fork":false,"pushed_at":"2023-02-15T17:43:34.000Z","size":8822,"stargazers_count":9,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-24T16:02:37.754Z","etag":null,"topics":["automl","automl-experiments","cybersecurity","iot","iot23","machine-learning","random-forest","svm"],"latest_commit_sha":null,"homepage":"","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/TryKatChup.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}},"created_at":"2023-01-04T13:06:10.000Z","updated_at":"2024-05-15T18:43:57.000Z","dependencies_parsed_at":null,"dependency_job_id":"9c0e2a82-069d-4153-9ca4-4a4cccebc45e","html_url":"https://github.com/TryKatChup/ML-IOT-malware-analysis","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TryKatChup%2FML-IOT-malware-analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TryKatChup%2FML-IOT-malware-analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TryKatChup%2FML-IOT-malware-analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TryKatChup%2FML-IOT-malware-analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/TryKatChup","download_url":"https://codeload.github.com/TryKatChup/ML-IOT-malware-analysis/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248270547,"owners_count":21075794,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["automl","automl-experiments","cybersecurity","iot","iot23","machine-learning","random-forest","svm"],"created_at":"2024-10-13T05:28:13.878Z","updated_at":"2025-04-10T18:22:14.631Z","avatar_url":"https://github.com/TryKatChup.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n\n# ML-IOT-malware-analysis\nMachine Learning models for IoT traffic malware detection. (Cybersecurity - Alma Mater Studiorum - University of Bologna)\n\u003c/div\u003e\n\n## Contents\n- [IoT23_preprocessing.ipynb](https://github.com/TryKatChup/ML-IOT-malware-analysis/blob/main/IoT23_preprocessing.ipynb): Jupyter Notebook with preprocessing operations, useful for both [tabular_prediction_AutoGluon.ipynb](https://github.com/TryKatChup/ML-IOT-malware-analysis/blob/main/autogluon/tabular_prediction_AutoGluon.ipynb) and [training_ML_models.ipynb](https://github.com/TryKatChup/ML-IOT-malware-analysis/blob/main/ml-classic/training_ML_models.ipynb).\n\n- [tabular_prediction_AutoGluon.ipynb](https://github.com/TryKatChup/ML-IOT-malware-analysis/blob/main/autogluon/tabular_prediction_AutoGluon.ipynb): Jupyter Notebook with AutoGluon Tabular experiments.\n\n- [training_ML_models.ipynb](https://github.com/TryKatChup/ML-IOT-malware-analysis/blob/main/ml-classic/training_ML_models.ipynb): Jupyter Notebook with classic Machine Learning Model training (random forest, SVM linear and with rbf kernel).\n\n- [reports](https://github.com/TryKatChup/ML-IOT-malware-analysis/tree/main/reports): my reports.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftrykatchup%2Fml-iot-malware-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftrykatchup%2Fml-iot-malware-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftrykatchup%2Fml-iot-malware-analysis/lists"}