國立高雄大學圖資館 |

登入

回首頁

Secure voice processing systems against malicious voice attacks

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Secure voice processing systems against malicious voice attacksby Kun Sun, Shu Wang.
作者:	Sun, Kun.
其他作者:	Wang, Shu.
出版者:	Cham :Springer Nature Switzerland :2024.
面頁冊數:	xvi, 111 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Speech processing systemsSecurity measures.
電子資源:	https://doi.org/10.1007/978-3-031-44748-8
ISBN:	9783031447488$q(electronic bk.)

Secure voice processing systems against malicious voice attacks
Sun, Kun.

Secure voice processing systems against malicious voice attacks[electronic resource] /by Kun Sun, Shu Wang. - Cham :Springer Nature Switzerland :2024. - xvi, 111 p. :ill., digital ;24 cm. - SpringerBriefs in computer science,2191-5776. - SpringerBriefs in computer science..

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 command attacks 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.

ISBN: 9783031447488$q(electronic bk.)

Standard No.: 10.1007/978-3-031-44748-8doiSubjects--Topical Terms:

971752
Speech processing systems
--Security measures.

LC Class. No.: TK7882.S65

Dewey Class. No.: 006.454

Secure voice processing systems against malicious voice attacks
LDR:02713nmm a2200325 a 4500 001 660414
003 DE-He213
005 20231030233230.0
006 m d
007 cr nn 008maaau
008 241106s2024 sz s 0 eng d
020 $a 9783031447488$q(electronic bk.)
020 $a 9783031447471$q(paper)
024 7 $a 10.1007/978-3-031-44748-8 $2 doi
035 $a 978-3-031-44748-8
040 $a GP $c GP
041 0 $a eng
050 4 $a TK7882.S65
072 7 $a URD $2 bicssc
072 7 $a COM060040 $2 bisacsh
072 7 $a URD $2 thema
082 0 4 $a 006.454 $2 23
090 $a TK7882.S65 $b S957 2024
100 1 $a Sun, Kun. $3 944830
245 1 0 $a Secure voice processing systems against malicious voice attacks $h [electronic resource] / $c by Kun Sun, Shu Wang.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a xvi, 111 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in computer science, $x 2191-5776
520 $a 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 command attacks 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 $a Speech processing systems $x Security measures. $3 971752
650 0 $a Voice computing $x Security measures. $3 971753
650 1 4 $a Privacy. $3 268519
650 2 4 $a Biometrics. $3 274525
700 1 $a Wang, Shu. $3 492901
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a SpringerBriefs in computer science. $3 559641
856 4 0 $u https://doi.org/10.1007/978-3-031-44748-8
950 $a Computer Science (SpringerNature-11645)