Scientometric Analysis Maps Global Cybersecurity Research Trends from 2000 to 2024

A comprehensive scientometric evaluation of global cybersecurity research spanning two and a half decades shows that scholarly production expanded dramatically from nominal beginnings in 2000 to an all-time peak of 1,852 peer-reviewed journal publications in 2023. Published in Discover Networks by researchers Reetu Verma, Nidhi Gupta, and Ashok Kumar, the investigation traced the trajectory of scholarly inquiry into digital security systems over the period from 2000 to 2024. By systematically mining bibliographic records and applying mathematical scientometric laws, the study established that scholarly output experienced a sustained surge after 2009. While publication counts climbed to their highest volume in 2023, citation accumulation achieved its maximum mark in 2021, when cybersecurity articles collectively accrued 24,456 citations across indexed journals.

To assemble an empirical corpus free from extraneous literature, the research team conducted a structured extraction from the Scopus database on August 6, 2024, utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework. The authors developed a targeted search string incorporating primary keywords such as cybersecurity, cyber attacks, cyber risks, cyber threats, information technology security, malware, phishing, and ransomware. Because broad queries across titles, abstracts, and author keywords often introduce false positives by capturing incidental mentions, the query was deliberately restricted to article titles. The screening protocol also excluded conference papers, book chapters, reviews, notes, editorials, and retracted items, while restricting results to final, English-language peer-reviewed journal articles published between 2000 and 2024. From an initial pool of 32,409 retrieved records, this rigorous filtration yielded a core dataset of 9,967 definitive journal articles.

The methodological framework coupled analytical software pipelines with empirical evaluations of three classical foundational theories in scientometrics: Bradford’s Law of Scattering, Lotka’s Law of Scientific Productivity, and Zipf’s Law of Keyword Occurrence. Data processing was conducted using RStudio’s Biblioshiny web interface alongside VOSviewer version 1.6.20 to visualize keyword co-occurrence patterns, institutional outputs, and transnational co-authorship networks. The authors pursued five structured research objectives: quantifying chronological publication and citation growth, identifying prolific authors and institutional contributors, evaluating journal impact, validating mathematical distribution models across the literature, and charting the conceptual structure of emerging technical themes.

Testing Bradford’s Law of Scattering assessed how cybersecurity literature distributes across 2,074 scientific publishing venues. Under theoretical conditions where journals are partitioned into three zones containing roughly equal numbers of articles in a 1 to n to n-squared ratio, a mean multiplier of 6.56 yielded an idealized distribution of 41 journals in the core nucleus, 269 journals in the intermediate zone, and 1,764 journals in the peripheral zone. The observed empirical count comprised 41 journals in Zone 1 carrying 3,293 papers, 267 journals in Zone 2 carrying 3,385 papers, and 1,766 journals in Zone 3 carrying 3,289 papers. With a theoretical journal prediction of 2,074.34 compared against the observed 2,074 journals, the resulting percentage error was calculated at just 0.02 percent, confirming that Bradford’s formulation accurately models the concentration of cybersecurity articles in core periodicals.

The evaluation of Lotka’s Law examined author productivity among 19,945 unique scholars indexed across the corpus using an inverse-power mathematical formulation. Applying linear least squares regression on a logarithmic scale generated a power-law exponent of 2.231. Goodness of fit was tested using the Kolmogorov-Smirnov statistical method, which established a critical threshold of 0.00963 at the 5 percent significance level based on the sample size. The observed maximum deviation of cumulative fractional frequencies was 0.004, well below the critical value. This lack of statistically significant discrepancy confirmed that Lotka’s Law governs the dataset, validating the structural tendency wherein a concentrated core of prolific specialists generates a disproportionate share of global research while the majority of authors publish single contributions.

The third empirical test applied Zipf’s Law to evaluate the frequency distribution of author keywords by ordering unique, normalized terms from highest to lowest occurrence. Log-log regression between keyword rank and occurrence frequency produced a regression line with a slope of negative 0.98, an intercept of 3.36, and a goodness-of-fit coefficient of determination of 0.98. The resulting power-law exponent of 0.98 demonstrated strict adherence to Zipfian mechanics, proving that a compact vocabulary of dominant technical terms anchors the literature, while a long tail of highly specialized concepts appears at low individual frequencies across the wider body of articles.

At the author level, performance metrics highlighted significant productivity among researchers affiliated with institutions in China, which accounted for ten of the top fifteen individual contributors. Across the top fifteen authors, cumulative output reached 798 papers and 27,395 citations. Individual publication volumes ranged between 21 and 90 documents. Scholar Wang Y achieved the highest absolute productivity with 90 published articles, while Liu Y demonstrated the greatest local impact with an h-index of 26 supported by 2,397 total citations, and Li Y achieved the highest g-index at 54. Institutional rankings corroborated this regional concentration: Sichuan University led globally with 199 indexed articles, followed closely by the Beijing University of Posts and Telecommunications with 183, the University of Electronic Science and Technology of China with 152, and King Abdulaziz University with 136 publications.

Country-level productivity showed that the United States and China formed the twin pillars of international scholarship, exhibiting distinct strengths in total output and citation influence. China achieved the highest frequency of author appearances at 6,086 accompanied by 26,675 citations, followed by the United States with 5,447 author appearances and 27,334 citations, and India with 3,269 appearances and 8,860 citations. When normalized using Field-Weighted Citation Impact metrics to reflect received citations against global expectations, the United Kingdom achieved the highest relative influence at 1.79, closely matched by the United States at 1.78, while China recorded an impact factor of 1.47 and India scored 0.89. Transnational collaboration mapping identified 88 interconnected nations clustered into eight cooperation networks, with Cluster 1 encompassing 24 predominantly European states and Cluster 6 linking China, the United States, Australia, and Singapore across 454 shared documents.

Analysis of dissemination channels indicated that 2,115 articles, representing 21.19 percent of global output, appeared within the top fifteen most prolific journals, accumulating 43,239 citations at an average of 20.44 citations per paper. IEEE Access led in sheer volume with 395 published papers and 8,799 citations, whereas Computers and Security stood out as the most impactful major outlet by average citation rate, averaging 31 citations per paper across 386 articles. Other prominent venues in Bradford’s core zone included Applied Sciences, Electronics, Computer Fraud and Security, and Security and Communication Networks. Among individual historical publications, a 2016 survey by Buczak in IEEE Communications Surveys and Tutorials registered the highest annual citation trajectory, maintaining a rate of 220.67 citations per year.

Mapping keyword co-occurrences and conceptual structures through Multiple Correspondence Analysis and thematic quadrants classified cybersecurity literature into four distinct operational domains. Motor themes—defined by high internal density and strong centrality—centered on core pillars including artificial intelligence, Internet of Things, security, and general cybersecurity, reflecting a systemic transition toward intelligent socio-technical defense frameworks. Basic themes exhibited high centrality but lower internal cohesion, spanning machine learning, deep learning, malware detection, ransomware, and Android systems. Niche topics formed an isolated pocket focused specifically on malware propagation, while emerging and declining themes clustered around social engineering, phishing attacks, anti-phishing countermeasures, and behavioral analytics.

The study also delineated several structural constraints inherent in the historical dataset and literature. By strictly analyzing Scopus-indexed journal articles, the investigation intentionally omitted computer science conference proceedings, which serve as rapid dissemination venues but differ in citation accumulation patterns. Furthermore, the bibliometric evidence revealed persistent regional fragmentation across international co-authorship networks, limited cross-disciplinary linkages connecting technical computer science to legal, ethical, and psychological fields, and an enduring deficit of deep analytical studies targeting fast-evolving frontiers such as Android malware ecosystems and artificial-intelligence-driven threat architectures.

Subject of Research: Scientometric and bibliometric analysis of global cybersecurity research literature from 2000 to 2024

Article Title: A comprehensive scientometric study of research trends in cybersecurity from 2000 to 2024 using Biblioshiny and VOSviewer

Article References: Verma, R., Gupta, N., & Kumar, A. (2025). A comprehensive scientometric study of research trends in cybersecurity from 2000 to 2024 using Biblioshiny and VOSviewer. Discover Networks, 1(1), Article 10. https://doi.org/10.1007/s44354-025-00011-0

Image Credits: AI Generated

DOI: 10.1007/s44354-025-00011-0

Keywords: Scientometrics, Bibliometrics, Cybersecurity Research, VOSviewer, Biblioshiny, Scopus Database, Bradford's Law, Lotka's Law, Zipf's Law, Co-authorship Networks, Network Security, Malware Detection, Machine Learning, Phishing, Computer Crime, Author Productivity