Izvorni znanstveni članak
https://doi.org/10.17535/crorr.2017.0017
Data anonymization patent landscape
Mirjana Pejić Bach
orcid.org/0000-0003-3899-6707
; Faculty of Economics and Business, University of Zagreb, J. F. Kennedy 6, 10 000 Zagreb, Croatia
Jasmina Pivar
; Faculty of Economics and Business, University of Zagreb, J. F. Kennedy 6, 10 000 Zagreb, Croatia
Ksenija Dumičić
orcid.org/0000-0001-7131-9455
; Faculty of Economics and Business, University of Zagreb, J. F. Kennedy 6, 10 000 Zagreb, Croatia
Sažetak
The omnipresent, unstoppable increase in digital data has led to a greater understanding of the importance of data privacy. Different approaches are used to implement data privacy. The goal of this paper is to develop a data anonymization patent landscape, by determining the following: (i) the trend in data anonymization patenting, (ii) the type of technical content protected in data anonymization, (iii) the organizations and countries most active in patenting data anonymization know-how; and (iv) the topics emerging most often in patent titles. Patents from the PatSeer database relating to data anonymization from 2001 to 2015 were analyzed. We used the longitudinal approach in combination with text mining techniques to develop a data anonymization patent landscape.
The results indicated the following. The number of single patent families is growing with a high increase after 2010, thus indicating a positive trend in the area of patenting data anonymization solutions. The majority of patenting activities relate to the G Physics section. Organizations from the USA and Japan assigned the majority of patents related to data anonymization. The results of text mining indicate that the most often used word in titles of data anonymization patents are “anonym*, “method”, “data” and “system”. Several additional words that indicated the most frequent topics related to data anonymization were: “equipment”, “software”, “protection”, “identification”, or “encryption”, and specific topics such as “community”, “medical”, or “service”.
Ključne riječi
data anonymization; patent landscape; PatSeer; data mining; association rules; text mining
Hrčak ID:
181676
URI
Datum izdavanja:
15.4.2017.
Posjeta: 1.459 *