単純な外見操作に対する顔年齢認証の脆弱性
Face Age Verification Vulnerabilities Under Simple Appearance Manipulations
オンラインプラットフォームの年齢認証システムが、口ひげや口紅などの簡単な外見操作でどの程度騙されるかを体系的に調査した論文。7つのモデルを3つのデータセットで評価し、特定の操作で最大61%の未成年が成人と誤認されることを示した。
著者: Ioannis Sarridis, Ioannis Kompatsiaris, Symeon Papadopoulos
分類: cs.CV
原文アブストラクト
Online platforms increasingly rely on automated age estimation systems to enforce minimum-age policies. Focusing on vision-based models designed for this task, concerns arise regarding their robustness to simple appearance changes that underage individuals may use to bypass such systems, such as drawing a mustache or applying lipstick. In this work, we present a systematic study of age verification robustness by simulating visual alterations that can be easily achieved by underage individuals. We evaluate seven models, including vision, vision-language, and multimodal large language models, across three datasets and four manipulation types. Interestingly, under drawn beard stubble, up to 61% of True Negatives are flipped into False Positives. Furthermore, we investigate how different demographics are affected by such manipulations, finding that Indians are more affected by beard stubble manipulations, while females are more affected than males across all manipulations. Finally, we explore how these biases can be mitigated using bias mitigation methodologies in lightweight linear probe settings.