{"year":"2013","citation":{"apa":"Stahl, K. (2013). AIS-based Anomaly Detection for Self-X Systems. <i>Proceedings of the First Organic Computing Doctoral Dissertation Colloquium (OC-DDC’13)</i>, 24–26.","short":"K. Stahl, in: Proceedings of the First Organic Computing Doctoral Dissertation Colloquium (OC-DDC’13), Reports / Technische Berichte - Herausgeber: Fakultät für Angewandte Informatik der Universität Augsburg, 2013, pp. 24–26.","bibtex":"@inproceedings{Stahl_2013, title={AIS-based Anomaly Detection for Self-X Systems}, booktitle={Proceedings of the First Organic Computing Doctoral Dissertation Colloquium (OC-DDC’13)}, publisher={Reports / Technische Berichte - Herausgeber: Fakultät für Angewandte Informatik der Universität Augsburg}, author={Stahl, Katharina}, year={2013}, pages={24–26} }","mla":"Stahl, Katharina. “AIS-Based Anomaly Detection for Self-X Systems.” <i>Proceedings of the First Organic Computing Doctoral Dissertation Colloquium (OC-DDC’13)</i>, Reports / Technische Berichte - Herausgeber: Fakultät für Angewandte Informatik der Universität Augsburg, 2013, pp. 24–26.","ieee":"K. Stahl, “AIS-based Anomaly Detection for Self-X Systems,” in <i>Proceedings of the First Organic Computing Doctoral Dissertation Colloquium (OC-DDC’13)</i>, 2013, pp. 24–26.","chicago":"Stahl, Katharina. “AIS-Based Anomaly Detection for Self-X Systems.” In <i>Proceedings of the First Organic Computing Doctoral Dissertation Colloquium (OC-DDC’13)</i>, 24–26. Reports / Technische Berichte - Herausgeber: Fakultät für Angewandte Informatik der Universität Augsburg, 2013.","ama":"Stahl K. AIS-based Anomaly Detection for Self-X Systems. In: <i>Proceedings of the First Organic Computing Doctoral Dissertation Colloquium (OC-DDC’13)</i>. Reports / Technische Berichte - Herausgeber: Fakultät für Angewandte Informatik der Universität Augsburg; 2013:24-26."},"page":"24-26","related_material":{"link":[{"url":"http://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/2355","relation":"confirmation"}]},"title":"AIS-based Anomaly Detection for Self-X Systems","date_updated":"2022-01-06T06:56:59Z","publisher":"Reports / Technische Berichte - Herausgeber: Fakultät für Angewandte Informatik der Universität Augsburg","date_created":"2021-10-04T12:45:34Z","author":[{"first_name":"Katharina","last_name":"Stahl","full_name":"Stahl, Katharina"}],"status":"public","type":"conference","publication":"Proceedings of the First Organic Computing Doctoral Dissertation Colloquium (OC-DDC'13)","language":[{"iso":"eng"}],"_id":"25298","user_id":"21240","department":[{"_id":"672"}]}