Secure Voice Processing Systems against Malicious Voice Attacks (Record no. 86921)

000 -LEADER
fixed length control field 06447nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-3-031-44748-8
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730170422.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 231030s2024 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031447488
-- 978-3-031-44748-8
082 04 - CLASSIFICATION NUMBER
Call Number 005.8
082 04 - CLASSIFICATION NUMBER
Call Number 323.448
100 1# - AUTHOR NAME
Author Sun, Kun.
245 10 - TITLE STATEMENT
Title Secure Voice Processing Systems against Malicious Voice Attacks
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2024.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVI, 111 p. 34 illus.
490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Computer Science,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 1 Introduction -- 1.1 Overview -- 1.2 Background -- 1.2.1 Audio Signal Processing -- 1.2.2 Voice Processing Systems -- 1.2.3 Attacks on Speaker Verification Systems -- 1.2.4 Attacks on Speech Recognition Systems -- 1.3 Book Structure -- References . . -- 2 Modulated Audio Replay Attack and Dual-Domain Defense -- 2.1 Introduction -- 2.2 Modulated Replay Attacks -- 2.2.1 Impacts of Replay Components -- 2.2.2 Attack Overview -- 2.2.3 Modulation Processor -- 2.2.4 Inverse Filter Estimation -- 2.2.5 Spectrum Processing -- 2.3 Countermeasure: Dual-domain Detection -- 2.3.1 Defense Overview -- 2.3.2 Time-domain Defense -- 2.3.3 Frequency-domain Defense -- 2.3.4 Security Analysis -- 2.4 Evaluation -- -- 2.4.1 Experiment Setup -- -- 2.4.2 Effectiveness of Modulated Replay Attacks -- 2.4.3 Effectiveness of Dual-Domain Detection -- 2.4.4 Robustness of Dual-Domain Detection -- 2.4.5 Overhead of Dual-Domain Detection -- 2.5 Conclusion -- -- Appendix 2.A: Mathematical Proof of Ringing Artifacts in Modulated Replay Audio -- -- Appendix 2.B: Parameters in Detection Methods -- Appendix 2.C: Inverse Filter Implementation -- Appendix 2.D: Classifiers in Time-Domain Defense -- References -- 3 Secure Voice Processing Systems for Driverless Vehicles -- 3.1 Introduction -- 3.2 Threat Model and Assumptions -- 3.3 System Design -- 3.3.1 System Overview -- 3.3.2 Detecting Multiple Speakers -- 3.3.3 Identifying Human Voice -- 3.3.4 Identifying Driver's Voice -- 3.4 Experimental Results -- 3.4.1 Accuracy on Detecting Multiple Speakers -- 3.4.2 Accuracy on Detecting Human Voice -- 3.4.3 Accuracy on Detecting Driver's Voice -- 3.4.4 System Robustness -- 3.4.5 Performance Overhead -- 3.5 Discussions -- 3.6 Conclusion -- References -- 4 Acoustic Compensation System against Adversarial Voice Recognition -- 4.1 Introduction -- 4.2 Threat Model -- 4.2.1 Spectrum Reduction Attack -- 4.2.2 Threat Hypothesis -- 4.3 System Design -- 4.3.1 Overview -- 4.3.2 Spectrum Compensation Module -- 4.3.3 Noise Addition Module -- 4.3.4 Adaptation Module -- 4.4 Evaluations -- 4.4.1 Experiment Setup -- 4.4.2 ACE Evaluation -- 4.4.3 Spectrum Compensation Module Evaluation -- 4.4.4 Noise Addition Module Evaluation -- 4.4.5 Adaptation Module Evaluation -- 4.4.6 Overhead -- 4.5 Residual Error Analysis -- 4.5.1 Types of ASR Inference Errors -- 4.5.2 Error Composition Analysis -- 4.6 Discussions -- 4.6.1 Multipath Effect and Audio Quality Improvement -- 4.6.2 Usability -- 4.6.3 Countering Attack Variants -- 4.6.4 Limitations -- 4.7 Conclusion -- Appendix 4.A: Echo Module -- Appendix 4.B: ACE Performance tested with CMU Sphinx -- Appendix 4.C: ACE Performance against Attack Variants -- References -- 5 Conclusion and Future Work -- 5.1 Conclusion -- 5.2 Future Work -- References.
520 ## - SUMMARY, ETC.
Summary, etc This book provides readers with the basic understanding regarding the threats to the voice processing systems, the state-of-the-art defense methods as well as the current research results on securing voice processing systems. It also introduces three mechanisms to secure the voice processing systems against malicious voice attacks under different scenarios, by utilizing time-domain signal waves, frequency-domain spectrum features and acoustic physical attributes. First, the authors uncover the modulated replay attack, which uses an inverse filter to compensate for the spectrum distortion caused by the replay attacks to bypass the existing spectrum-based defenses. The authors also provide an effective defense method that utilizes both the time-domain artifacts and frequency-domain distortion to detect the modulated replay attacks. Second, the book introduces a secure automatic speech recognition system for driverless car to defeat adversarial voice commandattacks launched from car loudspeakers, smartphones and passengers. Third, it provides an acoustic compensation system design to reduce the effects from the spectrum reduction attacks, by the audio spectrum compensation and acoustic propagation principle. Finally, the authors conclude with their research effort on defeating the malicious voice attacks and provide insights into more secure voice processing systems. This book is intended for security researchers, computer scientists and electrical engineers who are interested in the research areas of biometrics, speech signal processing, IoT security and audio security. Advanced-level students who are studying these topics will benefit from this book as well.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Law and legislation.
700 1# - AUTHOR 2
Author 2 Wang, Shu.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-44748-8
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer Nature Switzerland :
-- Imprint: Springer,
-- 2024.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data protection
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Biometric identification.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Privacy.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Biometrics.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2191-5776
912 ## -
-- ZDB-2-SCS
912 ## -
-- ZDB-2-SXCS

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