k-Nearest Neighborhood Structure (k-NNS) based alignment-free method for fingerprint template protection

2015 ◽  
Author(s):  
Mulagala Sandhya ◽  
Munaga V.N.K Prasad
Keyword(s):  
Neighborhood Structure ◽  
Alignment Free ◽  
Template Protection ◽  
Nearest Neighborhood

scholarly journals A New Design for Alignment-Free Chaffed Cancelable Iris Key Binding Scheme

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 164
Author(s):  
Tong-Yuen Chai ◽  
Bok-Min Goi ◽  
Yong-Haur Tay ◽  
and Zhe Jin
Keyword(s):  
Data Privacy ◽  
Iris Recognition ◽  
Large Scale ◽  
Security Analysis ◽  
Security And Privacy ◽  
Biometric Data ◽  
Alignment Free ◽  
Biometric Template ◽  
Significant Performance ◽  
Template Protection

Iris has been found to be unique and consistent over time despite its random nature. Unprotected biometric (iris) template raises concerns in security and privacy, as numerous large-scale iris recognition projects have been deployed worldwide—for instance, susceptibility to attacks, cumbersome renewability, and cross-matching. Template protection schemes from biometric cryptosystems and cancelable biometrics are expected to restore the confidence in biometrics regarding data privacy, given the great advancement in recent years. However, a majority of the biometric template protection schemes have uncertainties in guaranteeing criteria such as unlinkability, irreversibility, and revocability, while maintaining significant performance. Fuzzy commitment, a theoretically secure biometric key binding scheme, is vulnerable due to the inherent dependency of the biometric features and its reliance on error correction code (ECC). In this paper, an alignment-free and cancelable iris key binding scheme without ECC is proposed. The proposed system protects the binary biometric data, i.e., IrisCodes, from security and privacy attacks through a strong and size varying non-invertible cancelable transform. The proposed scheme provides flexibility in system storage and authentication speed via controllable hashed code length. We also proposed a fast key regeneration without either re-enrollment or constant storage of seeds. The experimental results and security analysis show the validity of the proposed scheme.

Neighborhood

2018 ◽  
Author(s):  
Emily Talen
Keyword(s):  
21St Century ◽  
Geographic Location ◽  
Social Contact ◽  
Neighborhood Structure ◽  
Urban Experience ◽  
Local Participation ◽  
Personal Influence ◽  
Social Mix ◽  
Traditional Sense ◽  
American Society

This book is written in support of those who believe that neighborhoods should be genuinely relevant in our lives, not as casual descriptors of geographic location but as places that provide an essential context for daily life. “Neighborhood” in its traditional sense—as a localized, place-based, delimited urban area that has some level of personal influence—seems a vanished part of the urban experience. This book explores whether 21st-century neighborhoods can once again provide a sense of caring and local participation and not devolve into enclaves seeking social insularity and separation. That the localized, diverse neighborhood has often failed to materialize requires thorough exploration. While many factors leading to the decline of the traditional neighborhood—e-commerce, suburban exclusivity, internet-based social contact—seem to be beyond anyone’s control, other factors seem more a product of neglect and confusion about neighborhood definition and its place in American society. Debates about the neighborhood have involved questions about social mix, serviceability, self-containment, centeredness, and connectivity within and without. This book works through these debates and proposes their resolution. The historical and global record shows that there are durable, time-tested regularities about neighborhoods. Many places outside of the West were built with neighborhood structure in evidence—long before professionalized, Western urban planning came on the scene. This book explores the compelling case that the American neighborhood can be connected to these traditions, anchored in human nature and regularities of form, and reinstated as something relevant and empowering in 21st-century urban experience.

scholarly journals Alignment-Free Sensing Module for Absolute and Incremental Lines in Linear Positioning System Based on Tunneling-Magnetoresistance Sensors

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4137
Author(s):  
Chia-Chang Lee ◽  
Yu-Shen Yen ◽  
Chih-Huang Lai
Keyword(s):  
Thin Film Deposition ◽  
Film Deposition ◽  
Alignment Error ◽  
Positioning System ◽  
Large Signal ◽  
Detection Scheme ◽  
Alignment Free ◽  
Reference Layer ◽  
Working Distance ◽  
Incremental Lines

An alignment-free sensing module for the positioning system based on tunneling magnetoresistive (TMR) sensors with an absolute-incremental-integrated scale is demonstrated. The sensors of the proposed system for both lines consist of identical layer stacks; therefore, all sensors can be fabricated in identical processes from thin film deposition to device patterning on a single substrate. Consequently, the relative position of the sensors can be predefined at the lithography stage and the alignment error between sensors caused by the manual installation is completely eliminated. Different from the existing sensing scheme for incremental lines, we proposed to utilize the magnetic tunnel junctions with a perpendicular anisotropy reference layer and an in-plane anisotropy sensing layer. The sensors are placed parallel to the scale plane with magnetization of the sensing layer in the plane, which show the capability of polarity detection for the absolute line and reveal sinusoidal output signal for the incremental line. Furthermore, due to the large signal of TMR, the working distance can be further improved compared with conventional sensors. In addition, the cost of the positioning system is expected to be lowered, since all the sensors are fabricated in the same process without extra installation. Our design may pave a new avenue for the positioning system based on a magnetic detection scheme.

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