A Bibliometric Analysis of Face Presentation Attacks based on Domain Adaptation

Background: This research aims to look into the work that has been done on Face Presentation attacks and detection with domain adaptation techniques from 2011 to 2021 utilizing bibliography methods. Approaches: Diverse research articles on Face Presentation Attacks were retrieved using the two most popular databases Web of Science & Scopus. Research articles consider between 2011-2021. Some research results, such as documents by year, documents by source, documents by funding agencies, countries, etc are obtained using Web of Science and Scopus Analyzers. The analysis is performed using Vos Viewer version 1.6.16 and various parameters such as keywords, co-authorship, co-occurrences, citation analysis, and so on. Results: We present findings for both the Web of Science and Scopus datasets in this paper. As a result of primary keywords as Face Presentation attacks and secondary keywords as domain adaptation-based Face anti-spoofing, the total no of documents is 117 and 151 respectively retrieved. The maximum number of documents are published in the year 2020, most of the research is carried out by China as it has maximum funding research agencies. Conclusions: The purpose of using two databases for analysis in this study is to reduce the efforts of research scholars in analyzing the two most popular databases separately. Research documents are analyzed based on various parameters indicates that the research topic has a very good potential. The network study of various parameters shows that there is a lot of space for contribution in terms of domain adaptation, generalization, adversarial attacks, GAN, machine learning, and deep learning in future research

A Bibliometric Survey on the Use of Long Short-Term Memory Networks for Multivariate Time series forecasting

In this paper, we aim to review and analyze the publications related to the utilization of Long Short-Term Memory (LSTM) networks for multivariate time series forecasting. The purpose of this bibliometric survey was to study how technology in the field of LSTM has evolved over the years. There were 242 research papers published, by over 50 researchers, over 6 years, on the topic of “Multivariate time series forecasting using LSTM”. The majority of these papers were published between the years 2018 and 2020. The Scopus database was utilized for analyzing recent trends in this area and to determine the model that would be best suited for weather forecasting applications. Through this study, we aim to shortlist various models that have shown consistent reliability and accuracy while utilizing multivariate time series data for prediction. These models can then be employed for other forecasting applications

Bibliometric survey on Zero-Knowledge Proof for Authentication

Background: Zero Knowledge Proof is a persuasive cryptographic protocol employed to provide data security by keeping the user\u27s identity, using the services anonymously. Zero Knowledge Proof can be the preferred option to use in multiple circumstances. Instead of using the public key cryptographic protocols, the zero-knowledge proof usage does not expose or leak confidential data or information during the transmission. Zero Knowledge Proof protocols are comparatively lightweight; this results in making it efficient in terms of memory. Zero Knowledge Proof applications can reside in authentication, identity management, cryptocurrency transactions, and many more. Traditional authentication schemes are vulnerable to attacks like password attacks, man-in-the-middle, replay attack, etc. while data transmission takes place over the network. Hence, there is a high need for developing an authentication scheme that does not leak the confidential information and provides authentication without disclosing the identity. Conclusion: In this paper the bibliometric study of Zero Knowledge Proof for Authentication is performed by using data extracted from the Scopus database. Observations are made based on this study that the maximum research publications on Zero Knowledge Proof for Authentication are from China, United States and India respectively. The conclusion of the paper is drawn that this specific research field is latest and research work in the coming years is necessary on Zero Knowledge Proof for Authentication