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Title

Mining digital identity insights: patent analysis using NLP.

Authors

Comb, Matthew; Martin, Andrew

Abstract

The field of digital identity innovation has grown significantly over the last 30 years, with over 6000 technology patents registered worldwide. However, many questions remain about who controls and owns our digital identity and intellectual property and, ultimately, where the future of digital identity is heading. To investigate this further, this research mines digital identity patents and explores core themes such as identity, systems, privacy, security, and emerging fields like blockchain, financial transactions, and biometric technologies, utilizing natural language processing (NLP) methods including part-of-speech (POS) tagging, clustering, topic classification, noise reduction, and lemmatisation techniques. Finally, the research employs graph modelling and statistical analysis to discern inherent trends and forecast future developments. The findings significantly contribute to the digital identity landscape, identifying key players, emerging trends, and technological progress. This research serves as a valuable resource for academia and industry stakeholders, aiding in strategic decision-making and investment in emerging technologies and facilitating navigation through the dynamic realm of digital identity technologies.

Subjects

TECHNOLOGICAL innovations; DIGITAL technology; NATURAL language processing; GRAPHIC methods in statistics; PATENTS; INTELLECTUAL property; BLOCKCHAINS

Publication

EURASIP Journal on Information Security, 2024, Vol 2024, Issue 1, p1

ISSN

1687-4161

Publication type

Academic Journal

DOI

10.1186/s13635-024-00172-5