Reif, Aliza Katharina und Stolz, Tarek und Picek, Stjepan und Ramirez Agudelo, Oscar Hernan und Karl, Michael (2025) The Image Scaling Attack: Unveiling the Risks in Traffic Sign Classification. In: 10th IEEE European Symposium on Security and Privacy Workshops, Euro S and PW 2025, Seiten 311-321. IEEE. 2025 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), 2025-06-30 - 2025-07-04, Venedig, Italien. doi: 10.1109/EuroSPW67616.2025.00041.
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Offizielle URL: https://ieeexplore.ieee.org/document/11129580
Kurzfassung
Image scaling attacks exploit vulnerabilities in the resizing process of deep learning-based vision systems, leading to severe misclassifications of the trained model. Such attacks pose a critical threat to automated traffic signal recognition systems, particularly in autonomous vehicles and intelligent traffic management. Indeed, autonomous vehicles must be able to adhere to traffic rules. As such, they need a reliable and robust traffic sign classification system. By using the German Traffic Sign Recognition Benchmark dataset and by building upon previous versions of image scaling attacks, this work implements clean-label and dirty-label experiments. As a result, this paper finds stronger attack methods than previously reported with over 90% accuracy, which are, at the same time, more difficult to detect. More precisely, we propose a novel clean-label image scaling attack that requires only small local changes to a part of the image. Furthermore, we demonstrate the versatility of the image scaling attack and show how the image scaling attack method is universally compatible with other backdoor and evasion attacks, as the approach can be applied independently of the actual attack. Finally, the real-world risks of the image scaling attack on traffic sign classification models are shown by replacing the computer-generated training trigger with a physical object at test time.
elib-URL des Eintrags: | https://elib.dlr.de/216274/ | ||||||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||||||
Titel: | The Image Scaling Attack: Unveiling the Risks in Traffic Sign Classification | ||||||||||||||||||||||||
Autoren: |
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Datum: | 1 September 2025 | ||||||||||||||||||||||||
Erschienen in: | 10th IEEE European Symposium on Security and Privacy Workshops, Euro S and PW 2025 | ||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||||||
DOI: | 10.1109/EuroSPW67616.2025.00041 | ||||||||||||||||||||||||
Seitenbereich: | Seiten 311-321 | ||||||||||||||||||||||||
Herausgeber: |
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Verlag: | IEEE | ||||||||||||||||||||||||
Name der Reihe: | IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) | ||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||
Stichwörter: | traffic sign classification, adversarial attacks, image scaling attack | ||||||||||||||||||||||||
Veranstaltungstitel: | 2025 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) | ||||||||||||||||||||||||
Veranstaltungsort: | Venedig, Italien | ||||||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||||||
Veranstaltungsbeginn: | 30 Juni 2025 | ||||||||||||||||||||||||
Veranstaltungsende: | 4 Juli 2025 | ||||||||||||||||||||||||
Veranstalter : | IEEE | ||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||
HGF - Programm: | Verkehr | ||||||||||||||||||||||||
HGF - Programmthema: | Straßenverkehr | ||||||||||||||||||||||||
DLR - Schwerpunkt: | Verkehr | ||||||||||||||||||||||||
DLR - Forschungsgebiet: | V ST Straßenverkehr | ||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | V - ACT4Transformation - Automated and Connected Technologies for Mobility Transformation | ||||||||||||||||||||||||
Standort: | Rhein-Sieg-Kreis | ||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für KI-Sicherheit | ||||||||||||||||||||||||
Hinterlegt von: | Reif, Aliza Katharina | ||||||||||||||||||||||||
Hinterlegt am: | 25 Sep 2025 09:15 | ||||||||||||||||||||||||
Letzte Änderung: | 25 Sep 2025 09:15 |
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