Playback Attack Detection: The Search for the Ultimate Set of Antispoof Features

Maciej Smiatacz

doi:10.1007/978-3-319-59162-9_13

Playback Attack Detection: The Search for the Ultimate Set of Antispoof Features

Abstract

Automatic speaker verification systems are vulnerable to several kinds of spoofing attacks. Some of them can be quite simple – for example, the playback of an eavesdropped recording does not require any specialized equipment nor knowledge, but still may pose a serious threat for a biometric identification module built into an e-banking application. In this paper we follow the recent approach and convert recordings to images, assuming that original voice can be distinguished from its played back version through the analysis of local texture patterns. We propose improvements to the state-of-the-art solution, but also show its severe limitations. This in turn leads to the fundamental question: is it possible to find one set of features which are characteristic for all playback recordings? We look for the answer by performing a series of optimization experiments, but in general the problem remains open.

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Category:: Monographic publication
Type:: rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
Title of issue:: Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017 strony 120 - 129
Language:: English
Publication year:: 2017
Bibliographic description:: Smiatacz M.: Playback Attack Detection: The Search for the Ultimate Set of Antispoof Features// / ed. Kurzynski M., Wozniak M., Burduk R. Cham: Springer, 2017, s.120-129
DOI:: Digital Object Identifier (open in new tab) 10.1007/978-3-319-59162-9_13
Verified by:: Gdańsk University of Technology