Mask-based Black-box Attacks on Safety-Critical Systems that Use Machine Learning:
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis Electronic eBook |
| Language: | English |
| Published: |
Erlangen ; Nürnberg
2021
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| Subjects: | |
| Online Access: | Volltext Volltext kostenfrei |
| Physical Description: | 1 Online-Ressource (vii, 142 Seiten) Illustrationen, Diagramme |
Staff View
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| 246 | 1 | 3 | |a Maskenbasierte Blackbox-Angriffe auf sicherheitskritische Systeme, die maschinelles Lernen verwenden |
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| spelling | Auernhammer, Katja (DE-588)1239187955 aut Mask-based Black-box Attacks on Safety-Critical Systems that Use Machine Learning vorgelegt von Katja Auernhammer Maskenbasierte Blackbox-Angriffe auf sicherheitskritische Systeme, die maschinelles Lernen verwenden Erlangen ; Nürnberg 2021 1 Online-Ressource (vii, 142 Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Dissertation Friedrich-Alexander-Universität Erlangen-Nürnberg 2021 Archivierung/Langzeitarchivierung gewährleistet DE-101 pdager Sicherheitskritisches System (DE-588)4767762-4 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Blackbox (DE-588)4539866-5 gnd rswk-swf 4\p Machine learning (DLC)sh85079324 http://id.loc.gov/authorities/subjects/sh85079324 lcsh Machine Learning Adversarial Machine Learning Adversarial Examples Universal Adversarial Perturbations Security Technical Debt Safety ASIL CVSS (DE-588)4113937-9 Hochschulschrift gnd-content Maschinelles Lernen (DE-588)4193754-5 s Blackbox (DE-588)4539866-5 s Sicherheitskritisches System (DE-588)4767762-4 s DE-604 https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-168921 Resolving-System kostenfrei Volltext https://d-nb.info/1238358292/34 Langzeitarchivierung Nationalbibliothek kostenfrei Volltext application/pdf https://open.fau.de/handle/openfau/16892 Verlag kostenfrei 1\p aepkn 0,97325 20210807 DE-101 https://d-nb.info/provenance/plan#aepkn 2\p aepsg 0,99809 20210807 DE-101 https://d-nb.info/provenance/plan#aepsg 3\p npi 20210806 DE-101 https://d-nb.info/provenance/plan#npi 4\p aeplcsh 0,07143 20210807 DE-101 https://d-nb.info/provenance/plan#aeplcsh |
| spellingShingle | Auernhammer, Katja Mask-based Black-box Attacks on Safety-Critical Systems that Use Machine Learning Sicherheitskritisches System (DE-588)4767762-4 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Blackbox (DE-588)4539866-5 gnd 4\p Machine learning (DLC)sh85079324 http://id.loc.gov/authorities/subjects/sh85079324 lcsh |
| subject_GND | (DE-588)4767762-4 (DE-588)4193754-5 (DE-588)4539866-5 (DLC)sh85079324 http://id.loc.gov/authorities/subjects/sh85079324 (DE-588)4113937-9 |
| title | Mask-based Black-box Attacks on Safety-Critical Systems that Use Machine Learning |
| title_alt | Maskenbasierte Blackbox-Angriffe auf sicherheitskritische Systeme, die maschinelles Lernen verwenden |
| title_auth | Mask-based Black-box Attacks on Safety-Critical Systems that Use Machine Learning |
| title_exact_search | Mask-based Black-box Attacks on Safety-Critical Systems that Use Machine Learning |
| title_exact_search_txtP | Mask-based Black-box Attacks on Safety-Critical Systems that Use Machine Learning |
| title_full | Mask-based Black-box Attacks on Safety-Critical Systems that Use Machine Learning vorgelegt von Katja Auernhammer |
| title_fullStr | Mask-based Black-box Attacks on Safety-Critical Systems that Use Machine Learning vorgelegt von Katja Auernhammer |
| title_full_unstemmed | Mask-based Black-box Attacks on Safety-Critical Systems that Use Machine Learning vorgelegt von Katja Auernhammer |
| title_short | Mask-based Black-box Attacks on Safety-Critical Systems that Use Machine Learning |
| title_sort | mask based black box attacks on safety critical systems that use machine learning |
| topic | Sicherheitskritisches System (DE-588)4767762-4 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Blackbox (DE-588)4539866-5 gnd 4\p Machine learning (DLC)sh85079324 http://id.loc.gov/authorities/subjects/sh85079324 lcsh |
| topic_facet | Sicherheitskritisches System Maschinelles Lernen Blackbox Machine learning Hochschulschrift |
| url | https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-168921 https://d-nb.info/1238358292/34 https://open.fau.de/handle/openfau/16892 |
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