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PhoneSpoof: A new dataset for spoofing attack detection in telephone channel

Abstract: 

The results of spoofing detection systems proposed during ASVspoof Challenges 2015 and 2017 confirmed the perspective in detection of unforseen spoofing trials in microphone channel. However, telephone channel presents much more challenging conditions for spoofing detection, due to limited bandwidth, various coding standards and channel effects. Research on the topic has thus far only made use of program codecs and other telephone channel emulations. Such emulations does not quite match the real telephone spoofing attacks. In order to asses spoofing detection methods in real scenario we present the PHONESPOOF dataset - spoofing data collected through realistic telephone channels. The PHONE-SPOOF data collection represents most threatening types of spoofing attacks and is publicly available dataset 1 . This work 2 aimed to investigate robustness of the state-of-the-art deep learning based antispoofing systems under telephone spoofing attacks conditions based on the PHONESPOOF data. Moreover newly collected dataset makes it possible to analize language dependency issue for the Anti-Spoofing methods. In the work we also focused on the development of a unified LCNN-based approach for spoofing attack detection. The goal was to train a single system able to detect various types of spoofing attacks in telephone channel. The obtained results approve the effectiveness of such solution.
https://ieeexplore.ieee.org/document/8682942

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Paper Details

Authors:
Galina Lavrentyeva, Sergey Novoselov, Marina Volkova, Yuri Matveev, Maria De Marsico
Submitted On:
7 May 2019 - 1:13pm
Short Link:
Type:
Poster
Event:
Presenter's Name:
Galina Lavrentyeva
Paper Code:
ICASSP19005
Document Year:
2019
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ICASSP-2019.pdf

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[1] Galina Lavrentyeva, Sergey Novoselov, Marina Volkova, Yuri Matveev, Maria De Marsico, "PhoneSpoof: A new dataset for spoofing attack detection in telephone channel", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3927. Accessed: Jul. 18, 2019.
@article{3927-19,
url = {http://sigport.org/3927},
author = {Galina Lavrentyeva; Sergey Novoselov; Marina Volkova; Yuri Matveev; Maria De Marsico },
publisher = {IEEE SigPort},
title = {PhoneSpoof: A new dataset for spoofing attack detection in telephone channel},
year = {2019} }
TY - EJOUR
T1 - PhoneSpoof: A new dataset for spoofing attack detection in telephone channel
AU - Galina Lavrentyeva; Sergey Novoselov; Marina Volkova; Yuri Matveev; Maria De Marsico
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3927
ER -
Galina Lavrentyeva, Sergey Novoselov, Marina Volkova, Yuri Matveev, Maria De Marsico. (2019). PhoneSpoof: A new dataset for spoofing attack detection in telephone channel. IEEE SigPort. http://sigport.org/3927
Galina Lavrentyeva, Sergey Novoselov, Marina Volkova, Yuri Matveev, Maria De Marsico, 2019. PhoneSpoof: A new dataset for spoofing attack detection in telephone channel. Available at: http://sigport.org/3927.
Galina Lavrentyeva, Sergey Novoselov, Marina Volkova, Yuri Matveev, Maria De Marsico. (2019). "PhoneSpoof: A new dataset for spoofing attack detection in telephone channel." Web.
1. Galina Lavrentyeva, Sergey Novoselov, Marina Volkova, Yuri Matveev, Maria De Marsico. PhoneSpoof: A new dataset for spoofing attack detection in telephone channel [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3927