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

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Main Authors: Tavazzi, Alessandro, David, Dimitri Percia, Jang-Jaccard, Julian, Mermoud, Alain
Format: Preprint
Published: 2024
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author Tavazzi, Alessandro
David, Dimitri Percia
Jang-Jaccard, Julian
Mermoud, Alain
author_facet Tavazzi, Alessandro
David, Dimitri Percia
Jang-Jaccard, Julian
Mermoud, Alain
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2403_01601
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Measuring Technological Convergence in Encryption Technologies with Proximity Indices: A Text Mining and Bibliometric Analysis using OpenAlex
Tavazzi, Alessandro
David, Dimitri Percia
Jang-Jaccard, Julian
Mermoud, Alain
Computers and Society
Cryptography and Security
Information Retrieval
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.
title Measuring Technological Convergence in Encryption Technologies with Proximity Indices: A Text Mining and Bibliometric Analysis using OpenAlex
topic Computers and Society
Cryptography and Security
Information Retrieval
url https://arxiv.org/abs/2403.01601