Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and ...Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.展开更多
Biometrics was identified as one amongst 10 emerging technologies which would change the world in the twenty-first century. Components and processes of biometric system and the relevant technologies are explained in t...Biometrics was identified as one amongst 10 emerging technologies which would change the world in the twenty-first century. Components and processes of biometric system and the relevant technologies are explained in this article. Examples of biometric applications and trends of biometric research, together with industry development, are introduced, which illustrate the challenges and opportunities of this technology.展开更多
Cancelable biometrics are a group of techniques to transform the input biometric to an irreversible feature intentionally using a transformation function and usually a key in order to provide security and privacy in b...Cancelable biometrics are a group of techniques to transform the input biometric to an irreversible feature intentionally using a transformation function and usually a key in order to provide security and privacy in biometric recognition systems.This transformation is repeatable enabling subsequent biometric comparisons.This paper introduces a new idea to be exploited as a transformation function for cancelable biometrics aimed at protecting templates against iterative optimization attacks.Our proposed scheme is based on time-varying keys(random biometrics in our case)and morphing transformations.An experimental implementation of the proposed scheme is given for face biometrics.The results confirm that the proposed approach is able to withstand leakage attacks while improving the recognition performance.展开更多
The handy biometric data is a double-edged sword,paving the way of the prosperity of biometric authentication systems but bringing the personal privacy concern.To alleviate the concern,various biometric template prote...The handy biometric data is a double-edged sword,paving the way of the prosperity of biometric authentication systems but bringing the personal privacy concern.To alleviate the concern,various biometric template protection schemes are proposed to protect the biometric template from information leakage.The preponderance of existing proposals is based on Hamming metric,which ignores the fact that predominantly deployed biometric recognition systems(e.g.face,voice,gait)generate real-valued templates,more applicable to Euclidean metric and Cosine metric.Moreover,since the emergence of similarity-based attacks,those schemes are not secure under a stolen-token setting.In this paper,we propose a succinct biometric template protection scheme to address such a challenge.The proposed scheme is designed for Euclidean metric and Cosine metric instead of Hamming distance.Mainly,the succinct biometric template protection scheme consists of distance-preserving,one-way,and obfuscation modules.To be specific,we adopt location sensitive hash function to realize the distance-preserving and one-way properties simultaneously and use the modulo operation to implement many-to-one mapping.We also thoroughly analyze the proposed scheme in three aspects:irreversibility,unlinkability and revocability.Moreover,comprehensive experiments are conducted on publicly known face databases.All the results show the effectiveness of the proposed scheme.展开更多
针对基于生物特征认证系统中的存储及传输安全问题,并且考虑到基于VQ(Vector Quantization)算法声纹认证系统训练数据少,存储空间和训练时间也比较小的优点,在基于VQ算法声纹认证系统的基础上,采用MRP(Multispace Random Projection)提...针对基于生物特征认证系统中的存储及传输安全问题,并且考虑到基于VQ(Vector Quantization)算法声纹认证系统训练数据少,存储空间和训练时间也比较小的优点,在基于VQ算法声纹认证系统的基础上,采用MRP(Multispace Random Projection)提出一种可撤销声纹模板.通过特征点与特征点,特征点与码字之间的距离变换前后保持不变,说明平均量化误差不变,从而证明该方法满足可撤销模板的性能保持性.通过随机矩阵和不定方程的分析证明该方法满足不可逆性,即是安全的.初步实验结果的认证率达96%,说明该方法的有效性.展开更多
基金funded by the National Natural Science Foundation of China(61991413)the China Postdoctoral Science Foundation(2019M651142)+1 种基金the Natural Science Foundation of Liaoning Province(2021-KF-12-07)the Natural Science Foundations of Liaoning Province(2023-MS-322).
文摘Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.
文摘Biometrics was identified as one amongst 10 emerging technologies which would change the world in the twenty-first century. Components and processes of biometric system and the relevant technologies are explained in this article. Examples of biometric applications and trends of biometric research, together with industry development, are introduced, which illustrate the challenges and opportunities of this technology.
基金This work was supported by PRIMA(No.H2020-MSCA-ITN-2019-860315)TRESPASS-ETN(No.H2020-MSCA-ITN-2019-860813)+1 种基金BBforTAI(No.PID2021-127641OB-I00 MICINN/FEDER)INTER-ACTION(No.PID2021-126521OB-I00 MICINN/FEDER).M.Ghafourian was supported by PRIMA and I.Serna was supported by an FPI fellowship from University Autonoma de Madrid,Spain.
文摘Cancelable biometrics are a group of techniques to transform the input biometric to an irreversible feature intentionally using a transformation function and usually a key in order to provide security and privacy in biometric recognition systems.This transformation is repeatable enabling subsequent biometric comparisons.This paper introduces a new idea to be exploited as a transformation function for cancelable biometrics aimed at protecting templates against iterative optimization attacks.Our proposed scheme is based on time-varying keys(random biometrics in our case)and morphing transformations.An experimental implementation of the proposed scheme is given for face biometrics.The results confirm that the proposed approach is able to withstand leakage attacks while improving the recognition performance.
文摘The handy biometric data is a double-edged sword,paving the way of the prosperity of biometric authentication systems but bringing the personal privacy concern.To alleviate the concern,various biometric template protection schemes are proposed to protect the biometric template from information leakage.The preponderance of existing proposals is based on Hamming metric,which ignores the fact that predominantly deployed biometric recognition systems(e.g.face,voice,gait)generate real-valued templates,more applicable to Euclidean metric and Cosine metric.Moreover,since the emergence of similarity-based attacks,those schemes are not secure under a stolen-token setting.In this paper,we propose a succinct biometric template protection scheme to address such a challenge.The proposed scheme is designed for Euclidean metric and Cosine metric instead of Hamming distance.Mainly,the succinct biometric template protection scheme consists of distance-preserving,one-way,and obfuscation modules.To be specific,we adopt location sensitive hash function to realize the distance-preserving and one-way properties simultaneously and use the modulo operation to implement many-to-one mapping.We also thoroughly analyze the proposed scheme in three aspects:irreversibility,unlinkability and revocability.Moreover,comprehensive experiments are conducted on publicly known face databases.All the results show the effectiveness of the proposed scheme.
文摘针对基于生物特征认证系统中的存储及传输安全问题,并且考虑到基于VQ(Vector Quantization)算法声纹认证系统训练数据少,存储空间和训练时间也比较小的优点,在基于VQ算法声纹认证系统的基础上,采用MRP(Multispace Random Projection)提出一种可撤销声纹模板.通过特征点与特征点,特征点与码字之间的距离变换前后保持不变,说明平均量化误差不变,从而证明该方法满足可撤销模板的性能保持性.通过随机矩阵和不定方程的分析证明该方法满足不可逆性,即是安全的.初步实验结果的认证率达96%,说明该方法的有效性.
