A Meta-analysis of Privacy, Ethical and Security Aspects of Facial Recognition Systems

2022 ◽  
Vol 16 (1) ◽  
pp. 0-0
Keyword(s):  
Facial Recognition ◽  
Meta Analysis ◽  
Privacy And Security ◽  
Systematic Analysis ◽  
Holistic Perspective ◽  
Facial Information ◽  
Security Challenges ◽  
Data Capturing ◽  
Recognition Systems ◽  
Advanced Computing

Facial recognition systems use advanced computing to capture facial information and compare the same with proprietary databases for validation. The emergence of data capturing intermediaries and open access image repositories have compounded the need for a holistic perspective for handling the privacy and security challenges associated with FRS. The study presents the results of a bibliometric analysis conducted on the topic of privacy, ethical and security aspects of FRS. This study presents the level of academic discussion on the topic using bibliometric performance analysis. The results of the bibliographic coupling analysis to identify the research hotspots are also presented. The results also include the systematic literature review of 148 publications that are distributed across seven themes. Both the bibliometric and systematic analysis showed that privacy and security in FRS requires a holistic perspective that cuts across privacy, ethical, security, legal, policy and technological aspects.

Facial recognition technologies and the new physiognomic era

2020 ◽  
Vol 43 (2) ◽  
pp. 45-56
Author(s):  
Abigail Nieves Delgado
Keyword(s):  
Facial Recognition ◽  
Personal Identification ◽  
Digital Photographs ◽  
Different Types ◽  
Recognition Systems ◽  
The Way

The current overproduction of images of faces in digital photographs and videos, and the widespread use of facial recognition technologies have important effects on the way we understand ourselves and others. This is because facial recognition technologies create new circulation pathways of images that transform portraits and photographs into material for potential personal identification. In other words, different types of images of faces become available to the scrutiny of facial recognition technologies. In these new circulation pathways, images are continually shared between many different actors who use (or abuse) them for different purposes. Besides this distribution of images, the categorization practices involved in the development and use of facial recognition systems reinvigorate physiognomic assumptions and judgments (e.g., about beauty, race, dangerousness). They constitute the framework through which faces are interpreted. This paper shows that, because of this procedure, facial recognition technologies introduce new and far-reaching »facialization« processes, which reiterate old discriminatory practices.

scholarly journals Security and Privacy Requirements for Electronic Consent

2021 ◽  
Vol 20 (2) ◽  
pp. 1-24
Author(s):  
Stef Verreydt ◽  
Koen Yskout ◽  
Wouter Joosen
Keyword(s):  
Security And Privacy ◽  
Inclusion Criteria ◽  
Comprehensive Overview ◽  
Privacy And Security ◽  
Pubmed Central ◽  
Privacy Requirements ◽  
Development Lifecycle ◽  
Main Challenge ◽  
Security Challenges ◽  
Server Systems

Electronic consent (e-consent) has the potential to solve many paper-based consent approaches. Existing approaches, however, face challenges regarding privacy and security. This literature review aims to provide an overview of privacy and security challenges and requirements proposed by papers discussing e-consent implementations, as well as the manner in which state-of-the-art solutions address them. We conducted a systematic literature search using ACM Digital Library, IEEE Xplore, and PubMed Central. We included papers providing comprehensive discussions of one or more technical aspects of e-consent systems. Thirty-one papers met our inclusion criteria. Two distinct topics were identified, the first being discussions of e-consent representations and the second being implementations of e-consent in data sharing systems. The main challenge for e-consent representations is gathering the requirements for a “valid” consent. For the implementation papers, many provided some requirements but none provided a comprehensive overview. Blockchain is identified as a solution to transparency and trust issues in traditional client-server systems, but several challenges hinder it from being applied in practice. E-consent has the potential to grant data subjects control over their data. However, there is no agreed-upon set of security and privacy requirements that must be addressed by an e-consent platform. Therefore, security- and privacy-by-design techniques should be an essential part of the development lifecycle for such a platform.

scholarly journals Facial Recognition System for People with and without Face Mask in Times of the COVID-19 Pandemic

2021 ◽  
Vol 13 (12) ◽  
pp. 6900
Author(s):  
Jonathan S. Talahua ◽  
Jorge Buele ◽  
P. Calvopiña ◽  
José Varela-Aldás
Keyword(s):  
Facial Recognition ◽  
Face Mask ◽  
Recognition System ◽  
Classification Model ◽  
World Health ◽  
The Face ◽  
Recognition Systems ◽  
Facial Recognition System ◽  
Health Organization ◽  
Face Detector

In the face of the COVID-19 pandemic, the World Health Organization (WHO) declared the use of a face mask as a mandatory biosafety measure. This has caused problems in current facial recognition systems, motivating the development of this research. This manuscript describes the development of a system for recognizing people, even when they are using a face mask, from photographs. A classification model based on the MobileNetV2 architecture and the OpenCv’s face detector is used. Thus, using these stages, it can be identified where the face is and it can be determined whether or not it is wearing a face mask. The FaceNet model is used as a feature extractor and a feedforward multilayer perceptron to perform facial recognition. For training the facial recognition models, a set of observations made up of 13,359 images is generated; 52.9% images with a face mask and 47.1% images without a face mask. The experimental results show that there is an accuracy of 99.65% in determining whether a person is wearing a mask or not. An accuracy of 99.52% is achieved in the facial recognition of 10 people with masks, while for facial recognition without masks, an accuracy of 99.96% is obtained.

Metastudie industrieller Energieflexibilität*/Meta-analysis of industrial energy flexibility - An approach for optimizing the identification of energy flexibility potentials

2017 ◽  
Vol 107 (09) ◽  
pp. 610-616
Author(s):  
S. Eisenhauer ◽  
F. Zimmermann ◽  
M. Reichart ◽  
P. Accordi ◽  
A. Prof. Sauer
Keyword(s):  
Production System ◽  
Meta Analysis ◽  
German Industry ◽  
Wird Eine ◽  
Bottom Up ◽  
Systematic Analysis ◽  
Industry Level ◽  
Large Spread ◽  
Industrial Energy ◽  
The Individual

Bisherige Studien über energetische Flexibilität in der deutschen Industrie weisen das vorhandene Flexibilitätspotenzial mit hoher Streuung aus. Diese Arbeit analysiert relevante Studien in Bezug auf deren Annahmen und Vorgehensweise. Aufbauend auf den bisherigen Vorgehensweisen wird ein Ansatz zur Erhebung der Daten im Produktionssystem vorgestellt. Des Weiteren wird eine Methode zur Aggregation der Daten hoch bis auf Branchenebene entwickelt.   Previous studies on the energetic flexibility of German industry show potentials with a large spread. Therefore, in this article, a systematic analysis of the individual studies and an evaluation of the indicated flexibility potentials are carried out. Based on the existing methods, a bottom-up approach for collecting the data in the production system and the aggregation up to the industry level is presented.

scholarly journals Systematic review and meta-analysis of the prevalence of coronavirus in the world: One health approach is urgent

2021 ◽  
Author(s):  
Ricardo Faustino ◽  
Miguel Faria ◽  
Monica Teixeira ◽  
Filipe Palavra ◽  
Maria Do Ceu Costa ◽  
...  
Keyword(s):  
Systematic Review ◽  
Fixed Effects ◽  
One Health ◽  
Animal Species ◽  
Meta Analysis ◽  
Epidemiological Surveillance ◽  
Forest Plot ◽  
Atypical Pneumonia ◽  
Systematic Analysis ◽  
Different Strains

Coronaviruses have been responsible for major epidemic crises in 2003 with SARS-CoV-1, in 2012 with MERS-CoV and in 2019 with SARS-CoV-2 (COVID-19), causing serious atypical pneumonia in humans. We intend, with this systematic analysis and meta-analysis, to clarify the prevalence of the various strains of coronavirus in different animal species. For this purpose, we carried out an electronic survey using Pubmed's Veterinary Science search tool to conduct a systematic assessment of published studies reporting the prevalence of different strains of coronavirus in different animal species between 2015 and 2020. We conducted different analysis to assess sensitivity, publication bias, and heterogeneity, using random and fixed effects. The final meta-analysis included 42 studies for systematic review and 29 in the meta-analysis. For the geographic regions with a prevalence greater than or equal to 0.20 (Forest plot overall; prevalence = 0.20, p < 0.01, Q = 10476.22 and I2 = 100%), the most commonly detected viruses were: enteric coronavirus (ECoV), pigeon-dominant coronavirus, (PdCoV), Avian coronavirus M41, Avian coronavirus C46, Avian coronavirus A99, Avian coronavirus JMK, MERS-CoV, Bovine coronavirus, Ro-BatCoV GCCDC1, Alphacoronavirus, Betacoronavirus, Deltacoronavirus, Gamacoronavirus and human coronaviruses (HCoVs). The wide presence of different strains of coronavirus in different animal species on all continents demonstrates the great biodiversity and ubiquity of these viruses. The most recent epidemiological crises caused by coronavirus demonstrates our unpreparedness to anticipate and mitigate emerging risks, as well as the need to implement new epidemiological surveillance programs for viruses. Combined with the need to create advanced training courses in One Health, this is paramount in order to ensure greater effectiveness in fighting the next pandemics.

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