Securable networked scheme with face authentication

IF 1.8 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IET Biometrics Pub Date : 2021-09-09 DOI:10.1049/bme2.12056

Da-You Huang, Chun-Liang Lin, Yang-Yi Chen

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引用次数: 3

Abstract

Recently, facial recognition has been extensively adopted in various fields. Wide applications are associated with a large amount of data transmission so that edge computing is inspired accordingly. In this research task, the major goal of edge computing is to handover a part of the computing work to the terminal equipment; the server only needs to process the results of final return. The IoT configuration proposed includes a perception layer, a transmission layer, and an application layer to fulfil a complete IoT system. In the perception layer, the facial authentication mechanism is adopted. This system is equipped with a highly robust anti-spoofing function, which can avoid criminal access from photos or electronic screens. Finally, the IoT transmission system is realised as the transmission layer. Combined with such a transmission mechanism, one can distribute user facial features to user's electronic devices instead of storing it in the server. This not only saves storage resources and transmission costs, but also allows users to complete data transmission and face authentication easily.

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具有人脸认证的安全网络方案

近年来，人脸识别技术已广泛应用于各个领域。广泛的应用与大量的数据传输相关联，从而激发了边缘计算。在本研究任务中，边缘计算的主要目标是将部分计算工作移交给终端设备;服务器只需要处理最终返回的结果。提出的物联网配置包括感知层、传输层和应用层，以实现一个完整的物联网系统。在感知层，采用了人脸认证机制。该系统配备了高度强大的防欺骗功能，可以避免犯罪分子通过照片或电子屏幕进入。最后，实现物联网传输系统作为传输层。结合这种传输机制，可以将用户的面部特征分发到用户的电子设备中，而不是存储在服务器中。这不仅节省了存储资源和传输成本，而且使用户可以轻松完成数据传输和面对认证。

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来源期刊

IET Biometrics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

5.90

自引率

0.00%

发文量

审稿时长

33 weeks

期刊介绍： The field of biometric recognition - automated recognition of individuals based on their behavioural and biological characteristics - has now reached a level of maturity where viable practical applications are both possible and increasingly available. The biometrics field is characterised especially by its interdisciplinarity since, while focused primarily around a strong technological base, effective system design and implementation often requires a broad range of skills encompassing, for example, human factors, data security and database technologies, psychological and physiological awareness, and so on. Also, the technology focus itself embraces diversity, since the engineering of effective biometric systems requires integration of image analysis, pattern recognition, sensor technology, database engineering, security design and many other strands of understanding. The scope of the journal is intentionally relatively wide. While focusing on core technological issues, it is recognised that these may be inherently diverse and in many cases may cross traditional disciplinary boundaries. The scope of the journal will therefore include any topics where it can be shown that a paper can increase our understanding of biometric systems, signal future developments and applications for biometrics, or promote greater practical uptake for relevant technologies: Development and enhancement of individual biometric modalities including the established and traditional modalities (e.g. face, fingerprint, iris, signature and handwriting recognition) and also newer or emerging modalities (gait, ear-shape, neurological patterns, etc.) Multibiometrics, theoretical and practical issues, implementation of practical systems, multiclassifier and multimodal approaches Soft biometrics and information fusion for identification, verification and trait prediction Human factors and the human-computer interface issues for biometric systems, exception handling strategies Template construction and template management, ageing factors and their impact on biometric systems Usability and user-oriented design, psychological and physiological principles and system integration Sensors and sensor technologies for biometric processing Database technologies to support biometric systems Implementation of biometric systems, security engineering implications, smartcard and associated technologies in implementation, implementation platforms, system design and performance evaluation Trust and privacy issues, security of biometric systems and supporting technological solutions, biometric template protection Biometric cryptosystems, security and biometrics-linked encryption Links with forensic processing and cross-disciplinary commonalities Core underpinning technologies (e.g. image analysis, pattern recognition, computer vision, signal processing, etc.), where the specific relevance to biometric processing can be demonstrated Applications and application-led considerations Position papers on technology or on the industrial context of biometric system development Adoption and promotion of standards in biometrics, improving technology acceptance, deployment and interoperability, avoiding cross-cultural and cross-sector restrictions Relevant ethical and social issues