Human respiratory infections caused by coronaviruses can range from mild to deadly. Although there are numerous studies on coronavirus disease 2019 (COVID-19), few have been published on its Omicron variant. In order to remedy this deficiency, this study undertook a bibliometric analysis of the publishing patterns of studies on the Omicron variant and identified hotspots. Automated transportation, environmental protection, improved healthcare, innovation in banking, and smart homes are just a few areas where machine learning has found use in tackling complicated problems. The sophisticated Scopus database was queried for papers with the term “Omicron” in the title published between January 2020 and June 2022. Microsoft Excel 365, VOSviewer, Bibliometrix, and Biblioshiny from R were used for a statistical analysis of the publications. Over the study period, 1917 relevant publications were found in the Scopus database. Viruses was the most popular in publications for Omicron variant research, with 150 papers published, while Cell was the most cited source. The bibliometric analysis determined the most productive nations, with USA leading the list with the highest number of publications (344) and the highest level of international collaboration on the Omicron variant. This study highlights scientific advances and scholarly collaboration trends and serves as a model for demonstrating global trends in Omicron variant research. It can aid policymakers and medical researchers to fully grasp the current status of research on the Omicron variant. It also provides normative data on the Omicron variant for visualization, study, and application.

Due to the advancement in industry 4.0, cybercrimes in internet‐based business applications are rapidly increasing. To encounter such attacks, the intruders use various tools and techniques such as Phishing, Malware, SQL Injection, Ransomware, Cross‐Site Scripting (XSS), Denial of Service (DoS), Session Hijacking, and Credential Reuse. Phishing is most commonly in practice in the current digital era. Phishing is a fraudulent attempt to obtain sensitive information from deceiving users. These types of cyber‐attacks are used to harm individuals or entire businesses depending on the targeted objective of the attacker. To combat these attacks, the research community provides various phishing detection techniques. In this article, we classify state‐of‐the‐art fishing detection techniques in five major categories, that are, (1) Data Mining, Deep Learning & Machine Learning‐Based Approach, (2) Search Engine‐Based Approach, (3) URL Scan‐Based Approach, (4) Blacklisting‐Whitelisting Approach, and (5) Visual Similarity‐Based Approach. Further, a comparative analysis is provided within each category concerning their strength and weaknesses. Moreover, the article provides phishing prevention best practices to the readers to avoid such attacks.

Rubella virus (RuV) generally causes a mild infection, but it can sometimes lead to systemic abnormalities. This study aimed to conduct a bibliometric analysis of over two decades of RuV research. Medical studies published from 2000 to 2021 were analyzed to gain insights into and identify research trends and outputs in RuV. R and VOSviewer were used to conduct a bibliometric investigation to determine the globally indexed RuV research output. The Dimensions database was searched with RuV selected as the subject, and 2500 published documents from the preceding two decades were reviewed. The number of publications on RuV has increased since 2003, reaching its peak in 2020. There were 12,072 authors and 16,769 author appearances; 88 publications were single-authored and 11,984 were multi-authored. The United States was the most influential contributor to RuV research, in terms of publications and author numbers. The number of RuV-related articles has continued to increase over the past few years due to the significant rubella burden in low-income nations. This study will aid in formulating plans and policies to control and prevent RuV infections.

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Background: This work aimed to undertake a bibliometric analysis of the Rubella virus. Medical studies were conducted between 2000 and 2022 to discover trends, dynamics, and research outputs in the industry. Methods:A bibliometric study was performed using R software to determine research characteristics indexed worldwide and published in Rubella research in medical studies. The Rubella virus was chosen as the subject in the PUBMED database, and 374 papers from the previous two decades were reviewed. Results: There was an increase in the number of publications after 2003. The United States was the most essential countryamong all which had the most contributions on Rubella Virus. Conclusion:Rubella research has increased in the medical profession over the previous decade, with the United States leading to publications in this field.