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Measuring Technological Convergence in Encryption Technologies with Proximity Indices: A Text Mining and Bibliometric Analysis using OpenAlex

Alessandro Tavazzi, Dimitri Percia David, Julian Jang-Jaccard, Alain Mermoud

TL;DR

This case study findings highlight a significant convergence between blockchain and public-key cryptography, evidenced by the increasing proximity indices, and offer valuable strategic insights for those contemplating investments in these domains.

Abstract

Identifying technological convergence among emerging technologies in cybersecurity is crucial for advancing science and fostering innovation. Unlike previous studies focusing on the binary relationship between a paper and the concept it attributes to technology, our approach utilizes attribution scores to enhance the relationships between research papers, combining keywords, citation rates, and collaboration status with specific technological concepts. The proposed method integrates text mining and bibliometric analyses to formulate and predict technological proximity indices for encryption technologies using the "OpenAlex" catalog. Our case study findings highlight a significant convergence between blockchain and public-key cryptography, evidenced by the increasing proximity indices. These results offer valuable strategic insights for those contemplating investments in these domains.

Measuring Technological Convergence in Encryption Technologies with Proximity Indices: A Text Mining and Bibliometric Analysis using OpenAlex

TL;DR

This case study findings highlight a significant convergence between blockchain and public-key cryptography, evidenced by the increasing proximity indices, and offer valuable strategic insights for those contemplating investments in these domains.

Abstract

Identifying technological convergence among emerging technologies in cybersecurity is crucial for advancing science and fostering innovation. Unlike previous studies focusing on the binary relationship between a paper and the concept it attributes to technology, our approach utilizes attribution scores to enhance the relationships between research papers, combining keywords, citation rates, and collaboration status with specific technological concepts. The proposed method integrates text mining and bibliometric analyses to formulate and predict technological proximity indices for encryption technologies using the "OpenAlex" catalog. Our case study findings highlight a significant convergence between blockchain and public-key cryptography, evidenced by the increasing proximity indices. These results offer valuable strategic insights for those contemplating investments in these domains.
Paper Structure (21 sections, 12 equations, 10 figures, 5 tables)

This paper contains 21 sections, 12 equations, 10 figures, 5 tables.

Figures (10)

  • Figure 1: Indices of proximity between Public-key cryptography and Blockchain from 2002 to 2021.
  • Figure 2: Optimal polynomial fitting of the time series of proximity indices between Public-key cryptography and Blockchain with an interpolation rate of 24% from 2002 to 2021.
  • Figure 3: Distribution of forecasting errors obtained by predicting time series of keyword-based proximity indices. The forecasting algorithm employed is Random Forest, trained globally on all our time series, with a forecasting horizon of 6 months
  • Figure 4: Case study: Examining the technological proximity between public-key cryptography and blockchain. The proximity indices undergo interpolation and are modeled using polynomial curves.
  • Figure 5: Evolution of the ratio between the number of citations and the number of published papers in the field of encryption technologies.
  • ...and 5 more figures