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@INCOLLECTION{Chingovska_SPRINGER_2016,
         author = {Chingovska, Ivana and Erdogmus, Nesli and Anjos, Andr{\'{e}} and Marcel, S{\'{e}}bastien},
       projects = {TABULA RASA},
          month = feb,
          title = {Face Recognition Systems Under Spoofing Attacks},
      booktitle = {Face Recognition Systems Under Spoofing Attacks},
        edition = {1st},
        chapter = {8},
           year = {2016},
          pages = {165-194},
      publisher = {Springer International Publishing},
           isbn = {978-3-319-28501-6},
            url = {http://link.springer.com/chapter/10.1007%2F978-3-319-28501-6_8},
            doi = {10.1007/978-3-319-28501-6_8},
       crossref = {Chingovska_Idiap-RR-18-2020},
       abstract = {In this chapter, we give an overview of spoofing attacks and spoofing countermeasures for face recognition systems , with a focus on visual spectrum systems (VIS) in 2D and 3D, as well as near-infrared (NIR) and multispectral systems . We cover the existing types of spoofing attacks and report on their success to bypass several state-of-the-art face recognition systems. The results on two different face spoofing databases in VIS and one newly developed face spoofing database in NIR show that spoofing attacks present a significant security risk for face recognition systems in any part of the spectrum. The risk is partially reduced when using multispectral systems. We also give a systematic overview of the existing anti-spoofing techniques, with an analysis of their advantages and limitations and prospective for future work.}
}



crossreferenced publications: 
@TECHREPORT{Chingovska_Idiap-RR-18-2020,
         author = {Chingovska, Ivana and Erdogmus, Nesli and Anjos, Andr{\'{e}} and Marcel, S{\'{e}}bastien},
       projects = {Idiap},
          month = {9},
          title = {Face Recognition Systems Under Spoofing Attacks},
           type = {Idiap-RR},
         number = {Idiap-RR-18-2020},
           year = {2020},
    institution = {Idiap},
           note = {Submitted for as a book-chapter for:  Face Recognition Across the Electromagnetic Spectrum (Springer)},
       abstract = {In this chapter we give an overview of spoofing attacks and spoofing
counter-measures for face recognition systems, in particular in a verification sce-
nario. We focus on 2D and 3D attacks to Visible Spectrum systems (VIS), as well
as Near Infrared (NIR) and multispectral systems. We cover the existing types of
spoofing attacks and report on their success to bypass several state-of-the-art face
verification systems. The results on two different face spoofing databases with VIS
attacks and one newly developed face spoofing database with VIS and NIR attacks,
show that spoofing attacks present a significant security threat for face verification
systems in any part of the spectrum. The risk is partially reduced when using mul-
tispectral systems. We also give a systematic overview of the existing anti-spoofing
techniques, with an analysis of their advantages and limitations and prospectives for
future work.},
            pdf = {https://publications.idiap.ch/attachments/reports/2015/Chingovska_Idiap-RR-18-2020.pdf}
}