Face Biometrics Under Spoofing Attacks: Vulnerabilities, Countermeasures, Open Issues, and Research Directions

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Statistical Meta-Analysis of Presentation Attacks for Secure Multibiometric Systems (2016, background): “For instance, in [48], it has been claimed that it is not possible to forecast all potential face spoofing attacks and fake fabrication techniques, as humans can always find very creative ways to cheat a system.”
Presentation Attack Detection Methods for Face Recognition Systems (2017, background): “…can provide insight into both the vulnerability of data capture subsystems and presentation attack detection methods in face recognition systems [Hadid 2014; Galbally et al. 2014a], publicly available databases [Tan et al. 2010; Anjos and Marcel 2011; Chingovska et al. 2012; Zhang et al. 2012],…”
Designing a Moral Compass for the Future of Computer Vision Using Speculative Analysis (2017, unknown): “Other research has proven that these adversarial inputs are not simply laboratory scenarios, but expose a reality of real-world vulnerabilities [38, 27].”
Deep Models and Shortwave Infrared Information to Detect Face Presentation Attacks (2020, background): “Nevertheless, there exists many studies showing that current face recognition algorithms are not robust to face presentation attacks [1], [2], [3], [4], [5].”
On the vulnerability of extended Multispectral face recognition systems towards presentation attacks (2017, methodology): “Thus, it is naturally assumed that the multispectral sensors are resistant to different kinds of PAIs.”