Logo des Repositoriums
 

Toward Practical Adversarial Attacks on Face Verification Systems

Kurzanzeige
dc.contributor.authorKakizaki, Kazuya
dc.contributor.authorMiyagawa, Taiki
dc.contributor.authorSingh, Inderjeet
dc.contributor.authorSakuma, Jun
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.contributor.editorDamer, Naser
dc.contributor.editorDantcheva, Antitza
dc.contributor.editorGomez-Barrero, Marta
dc.contributor.editorRaja, Kiran
dc.contributor.editorRathgeb, Christian
dc.contributor.editorSequeira, Ana
dc.contributor.editorUhl, Andreas
dc.date.accessioned2021-10-04T08:43:43Z
dc.date.available2021-10-04T08:43:43Z
dc.date.issued2021
dc.description.abstractDNN-based face verification systems are vulnerable to adversarial examples. The previous paper's evaluation protocol (scenario), which we called the probe-dependent attack scenario, was unrealistic. We define a more practical attack scenario, the probe-agnostic attack. We empirically show that these attacks are more challenging than probe-dependent ones. We propose a simple and effective method, PAMTAM, to improve the attack success rate for probe-agnostic attacks. We show that PAMTAM successfully improves the attack success rate in a wide variety of experimental settings.en
dc.identifier.isbn978-3-88579-709-8
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/37446
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-315
dc.subjectAdversarial example
dc.subjectFace verification
dc.subjectSecurity
dc.titleToward Practical Adversarial Attacks on Face Verification Systemsen
dc.typeText/Conference Paper
gi.citation.endPage124
gi.citation.publisherPlaceBonn
gi.citation.startPage113
gi.conference.date15.-17. September 2021
gi.conference.locationInternational Digital Conference
gi.conference.sessiontitleRegular Research Papers

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild
Name:
biosig2021_proceedings_12.pdf
Größe:
422.71 KB
Format:
Adobe Portable Document Format
Herunterladen

Sammlungen

P315 - BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group