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@INCOLLECTION{Chingovska_SPRINGER-2_2014,
                      author = {Chingovska, Ivana and Anjos, Andr{\'{e}} and Marcel, S{\'{e}}bastien},
                      editor = {Z.Li, Stan and Jain, Anil},
                    projects = {TABULA RASA},
                       title = {Anti-spoofing: Evaluation Methodologies},
                   booktitle = {Encyclopedia of Biometrics},
                     edition = {2nd edition},
                        year = {2014},
                   publisher = {Springer US},
                        isbn = {978-3-642-27733-7},
                         doi = {10.1007/978-3-642-27733-7},
                    abstract = {Following the definition of the task of the anti-spoofing systems to discriminate between real accesses and spoofing attacks, anti-spoofing can be regarded as a binary classification problem. The spoofing databases and the evaluation methodologies for anti-spoofing systems most often comply to the standards for binary classification problems. However, the anti-spoofing systems are not destined to work stand-alone, and their main purpose is to protect a verification system from spoofing attacks. In the process of combining the decision of an anti-spoofing and a recognition system, effects on the recognition performance can be expected. Therefore, it is important to analyze the problem of anti-spoofing under the umbrella of biometric recognition systems. This brings certain requirements in the database design, as well as adapted concepts for evaluation of biometric recognition systems under spoofing attacks.}
}