Biometrics Based Privacy‐Preserving Authentication and Mobile Template Protection

Yang, Wencheng; Hu, Jiankun; Wang, Song; Wu, Qianhong

doi:10.1155/2018/7107295

Cited by 24 publications

(14 citation statements)

References 53 publications

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“…The proposed scheme achieves the best performance when the length of the feature vector is set to 1024 bits and provides strong data privacy and security. Yang et al [48] designed a cancelable fingerprint template based on random projection. The designed template can defend attacks via record multiplicity (ARM) owing to the feature decorrelation algorithm.…”

Section: Cancelable Biometricsmentioning

confidence: 99%

“…There are two categories in the design of cancelable biometrics. One category centers around the extraction and representation of stable biometric features [36][37][38]48] so as to achieve better recognition accuracy, and the other category focuses on designing secure transformation functions, which are expected to be mathematically non-invertible [39][40][41][42]46]. It is anticipated that future research work in cancelable biometrics will attempt to achieve both better recognition accuracy and stronger security by using multiple cancelable biometrics.…”

Section: Cancelable Biometricsmentioning

confidence: 99%

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Security and Accuracy of Fingerprint-Based Biometrics: A Review

et al. 2019

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Biometric systems are increasingly replacing traditional password-and token-based authentication systems. Security and recognition accuracy are the two most important aspects to consider in designing a biometric system. In this paper, a comprehensive review is presented to shed light on the latest developments in the study of fingerprint-based biometrics covering these two aspects with a view to improving system security and recognition accuracy. Based on a thorough analysis and discussion, limitations of existing research work are outlined and suggestions for future work are provided. It is shown in the paper that researchers continue to face challenges in tackling the two most critical attacks to biometric systems, namely, attacks to the user interface and template databases. How to design proper countermeasures to thwart these attacks, thereby providing strong security and yet at the same time maintaining high recognition accuracy, is a hot research topic currently, as well as in the foreseeable future. Moreover, recognition accuracy under non-ideal conditions is more likely to be unsatisfactory and thus needs particular attention in biometric system design. Related challenges and current research trends are also outlined in this paper. recognition as an example. In the stage of enrollment, a user presents their finger to the fingerprint sensor and a fingerprint image is acquired by the sensor module. Certain features of the acquired fingerprint image are extracted, and further adapted or transformed to generate template data for the purpose of comparison in the verification stage. In the verification stage, the fingerprint image of a query is collected by the sensor module. The feature representations of the query fingerprint image go through the same process as in the enrollment stage, so as to obtain query data. The query data are then compared with the template data so that a matching outcome is attained.

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Section: Cancelable Biometricsmentioning

confidence: 99%

Section: Cancelable Biometricsmentioning

confidence: 99%

Security and Accuracy of Fingerprint-Based Biometrics: A Review

et al. 2019

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“…Although all of the above schemes and many other recent schemes [22][23][24] have suggested security improvements, there still remain drawbacks with regard to their protocols, as summarized in Table 1, such that a session key is not established after user authentication and message confidentiality is not considered. In addition, these protocols require extra hardware and are vulnerable to different types of DOS attacks.…”

Section: Literature Reviewmentioning

confidence: 99%

SUBBASE: An Authentication Scheme for Wireless Sensor Networks Based on User Biometrics

Riaz

Gillani

Rizvi

et al. 2019

Wireless Communications and Mobile Computing

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To keep a network secure, a user authentication scheme that allows only authenticated users to access network services is required. However, the limited resources of sensor nodes make providing authentication a challenging task. We therefore propose a new method of security for a wireless sensor network (WSN). Our technique, Secure User Biometric Based Authentication Scheme (SUBBASe), is based on the user biometrics for WSNs. It achieves a higher security level as well as improved network performance. This solution consists of easy operations and light computations. Herein, the proposed technique is evaluated and compared with previous existing techniques. This scheme increases the performance of the network by reducing network traffic, defending against DOS attacks, and increasing the battery life of a node. Consequently, the functionality and performance of the entire network is improved.

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“…Research efforts have been dedicated to the construction of more precise, usable and secure biometric authentication mechanisms. Feature de-correlation algorithm was designed for analyzing security aspects along with mechanisms to combat against several attacks [12]. Jun Xu et al proposed hand gesture recognition method using pictorial structure and edge information for ensuring accuracy under complex backgrounds, but interoperability rate and flexibility was said to be compromised.…”

Section: Related Workmentioning

confidence: 99%

Histogram of Neighborhood Tripartite Authentication with Fingerprint-based Biometrics for IoT Services

Kanchana¹

2019

IJCNC

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Internet of Things (IoT) and services is an interesting topic with a wide range of potential applications like smart home systems, health care, telemedicine, and intelligent transportation. Traditionally, key agreement schemes have been evaluated to access IoT services which are highly susceptible to security. Recently, Biometric-based authentication is also used to access IoT services and devices. They are involving a larger amount of memory with increased running time and found to be computationally infeasible. To provide robust authentication for IoT services, Histogram of Neighborhood Tripartite Authentication with Fingerprint Biometrics (HNTA-FB) for IoT services is proposed in this paper. This proposed HNTA-FB method uses binary patterns and a histogram of features to extract the region of interest. To reduce the memory requirements while providing access to IoT services, Histogram of Neighborhood Binary Pattern Pre-processing (HNBPP) model is proposed. The discriminative power of Neighbourhood Binary Pattern Registration (NBPR) is integrated with the normalized sparse representation based on the histogram. Additionally, this work presents a new Tripartite User Authentication model for fingerprint biometric template matching process. When compared with different state-of-the-art methods, the proposed method depicts significantly improved performance in terms of matching accuracy, computational overhead and execution speed and is highly effective in delivering smart home services.

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Biometrics Based Privacy‐Preserving Authentication and Mobile Template Protection

Cited by 24 publications

References 53 publications

Security and Accuracy of Fingerprint-Based Biometrics: A Review

Security and Accuracy of Fingerprint-Based Biometrics: A Review

SUBBASE: An Authentication Scheme for Wireless Sensor Networks Based on User Biometrics

Histogram of Neighborhood Tripartite Authentication with Fingerprint-based Biometrics for IoT Services

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