Long sequence biometric hashing authentication based on 2D-SIMM and CQCC cosine values

doi:10.1007/s11042-021-11708-z

IR > 计算机与通信学院

	Long sequence biometric hashing authentication based on 2D-SIMM and CQCC cosine values
	Huang, Yi-bo 1; Hou, Hexiang 1; Chen, Tengfei 1; Li, Hao 1; Zhang, Qiu-yu2
	2022-01
发表期刊	MULTIMEDIA TOOLS AND APPLICATIONS
ISSN	1380-7501
卷号	81 期号:2 页码:2873-2899
摘要	The existing speech authentication algorithms hash extracted speech features directly and saved them to the cloud, which is easy to cause speech feature leakage. In the process of constructing hashing, the utilization efficiency of speech feature is poor, and the short hashing sequence will lead to the lack of discrimination of hashing sequence and the deviation of authentication. In order to solve the above problems, a long sequence biometric hashing authentication algorithm based on two-dimensional Sine ICMI Cmodulation map (2D-SIMM) and constant Q cepstral coefficients (CQCC) cosine was proposed. First, this algorithm extracts the CQCC of the speech signal, then obtains the eigenvalue of the space cosine distance of the adjacent speech frame CQCC, and finally performs projection mapping between the eigenvalue and the pseudorandom matrix generated by 2D-SIMM to construct a biometric hashing sequence. This paper evaluates the proposed robust feature schemes of MFCC and CQCC space cosine distance through experiments. The experimental results show that CQCC spatial distance combined with 2D-SIMM biometrics characteristics can reach 10(-21). when the threshold is 0.35. The BER mean was only 0.0383 for maintaining the robustness of operation for different contents. When the SNR is -5 dB, the matching rate of different noises can reach 45%. At the same time, it also improves the security of the biological template, and the overall performance is greatly improved compared with the existing algorithm.
关键词	Speech content authentication Biometric security template 2D-SIMM CQCC cosine Discrimination Unidirectional
DOI	10.1007/s11042-021-11708-z
收录类别	SCIE ; EI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000715720000001
出版者	SPRINGER
EI入藏号	20214511135660
EI主题词	Eigenvalues and eigenfunctions
EI分类号	461 Bioengineering and Biology ; 461.8.2 Bioinformatics ; 723 Computer Software, Data Handling and Applications ; 751.5 Speech
来源库	WOS
引用统计	被引频次[WOS]：0 [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/150082
专题	计算机与通信学院
通讯作者	Huang, Yi-bo
作者单位	1.Northwest Normal Univ, Coll Phys & Elect Engn, Lanzhou 730070, Peoples R China; 2.Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Peoples R China
推荐引用方式 GB/T 7714	Huang, Yi-bo,Hou, Hexiang,Chen, Tengfei,et al. Long sequence biometric hashing authentication based on 2D-SIMM and CQCC cosine values[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2022,81(2):2873-2899.
APA	Huang, Yi-bo,Hou, Hexiang,Chen, Tengfei,Li, Hao,&Zhang, Qiu-yu.(2022).Long sequence biometric hashing authentication based on 2D-SIMM and CQCC cosine values.MULTIMEDIA TOOLS AND APPLICATIONS,81(2),2873-2899.
MLA	Huang, Yi-bo,et al."Long sequence biometric hashing authentication based on 2D-SIMM and CQCC cosine values".MULTIMEDIA TOOLS AND APPLICATIONS 81.2(2022):2873-2899.

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