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@INCOLLECTION{Anjos_SPRINGER_2019,
         author = {Anjos, Andr{\'{e}} and Tome, Pedro and Marcel, S{\'{e}}bastien},
         editor = {Marcel, S{\'{e}}bastien and Nixon, Mark and Fierrez, Julian and Evans, Nicholas},
       projects = {Idiap, 3DFINGERVEIN},
          title = {An Introduction to Vein Presentation Attacks and Detection},
      booktitle = {Handbook of Biometric Anti-Spoofing},
        edition = {2nd},
        chapter = {18},
           year = {2019},
      publisher = {Springer International Publishing},
           isbn = {978-3-319-92627-8},
            url = {https://www.springer.com/us/book/9783319926261},
            doi = {10.1007/978-3-319-92627-8},
       abstract = {The domain of presentation attacks (PA), including vulnerability studies and detection (PAD) remains very much unexplored by available scientific literature in biometric vein recognition. Contrary to other modalities that use visual spectral sensors for capturing biometric samples, vein biometrics is typically implemented with near-infrared imaging. The use of invisible light spectra challenges the cre- ation PA instruments, but does not render it impossible. In this chapter, we provide an overview of current landscape for PA manufacturing in possible attack vectors for vein recognition, describe existing public databases and baseline techniques to counter such attacks. The reader will also find material to reproduce experiments and findings for fingervein recognition systems. We provide this material with the hope it will be extended to other vein recognition systems and improved in time.}
}