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

Conference paper

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

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 578)
Cite this paper as:
Smiatacz M. (2018) Playback Attack Detection: The Search for the Ultimate Set of Antispoof Features. In: Kurzynski M., Wozniak M., Burduk R. (eds) Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017. CORES 2017. Advances in Intelligent Systems and Computing, vol 578. Springer, Cham

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.

Keywords

Playback detection Antispoof algorithms Biometrics 

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Faculty of Electronics, Telecommunications and InformaticsGdańsk University of TechnologyGdańskPoland

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