engleski

Data anonymization patent landscape

The omnipresence of the digital data that is unstoppably increasing has raised the understanding of the importance of the data privacy. Since data is stored in various data storages, different approaches are used in order to protect the privacy of the subjects related to the data. Goal of this paper is to develop a data anonymization patent landscape, by providing the answers to the following issues: (i) what is the trend in data anonymization patenting, (ii) what technical content for the data anonymization is protected, (iii) which organizations and countries were most active in patenting data anonymization know-how ; and (iv) what themes emerge the most often in the patent titles. Patents from the PatSeer database related to the data anonymization from 2001 to 2015 were analyzed. Longitudinal approach in combination with text mining techniques was utilized in order to develop a data anonymization patent landscape. Results indicated the following. The number of Single Patent Families is growing with the high increase after 2010, and especially after 2014, thus indicating a positive trend in the area of patenting data anonymization solutions. The majority of simple patent families related to data anonymization were assigned to the section G Physics. According to the patent analysis, the data anonymization technology is spread across different countries, but the majority of simple patent families related to data anonymization have been assigned by the USA and Japan organizations. Results of the text mining indicates that the most often used word in titles of the patents related to data anonymization was “anonym*, followed by “method”, “data” and “system”. Several additional groups that indicated the most often themes related to data anonymization were detected: physical equipment, software, protection, identification, encryption or privacy, and specific themes such as community, medical, or service. Limitations of this work result from the fact that we have oriented only to the simple patent families that have the word “data” and one of the following words: “anonymizing“, “anonymization”, “anonymized”, “anonymizy” and “anonymize”. Hence, the patents that have these words in the abstract, but not in the title are omitted from the analysis. Further research recommendations emerge from these limitations, urging the need to include also the abstract and full text into the analysis. Since this would lead to the much larger number of results, text mining approach should be fully utilized for such a research in order to automatize the process of analysis.

Data anonymization; Patent landscape; PatSeer; Data mining; Association rules; Text mining

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