Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Automated data-driven profiling: threats for group privacy

Automated data-driven profiling: threats for group privacy User profiling with big data raises significant issues regarding privacy. Privacy studies typically focus on individual privacy; however, in the era of big data analytics, users are also targeted as members of specific groups, thus challenging their collective privacy with unidentified implications. Overall, this paper aims to argue that in the age of big data, there is a need to consider the collective aspects of privacy as well and to develop new ways of calculating privacy risks and identify privacy threats that emerge.Design/methodology/approachFocusing on a collective level, the authors conducted an extensive literature review related to information privacy and concepts of social identity. They also examined numerous automated data-driven profiling techniques analyzing at the same time the involved privacy issues for groups.FindingsThis paper identifies privacy threats for collective entities that stem from data-driven profiling, and it argues that privacy-preserving mechanisms are required to protect the privacy interests of groups as entities, independently of the interests of their individual members. Moreover, this paper concludes that collective privacy threats may be different from threats for individuals when they are not members of a group.Originality/valueAlthough research evidence indicates that in the age of big data privacy as a collective issue is becoming increasingly important, the pluralist character of privacy has not yet been adequately explored. This paper contributes to filling this gap and provides new insights with regard to threats for group privacy and their impact on collective entities and society. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Information and Computer Security Emerald Publishing

Automated data-driven profiling: threats for group privacy

Mavriki, Paola; Karyda, Maria
Information and Computer Security , Volume 28 (2): 15 – Nov 7, 2019
Download PDF
15 pages

Loading next page...
 
/lp/emerald-publishing/automated-data-driven-profiling-threats-for-group-privacy-74bRwsauXM

References (79)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
2056-4961
eISSN
2056-4961
DOI
10.1108/ics-04-2019-0048
Publisher site
See Article on Publisher Site

Abstract

User profiling with big data raises significant issues regarding privacy. Privacy studies typically focus on individual privacy; however, in the era of big data analytics, users are also targeted as members of specific groups, thus challenging their collective privacy with unidentified implications. Overall, this paper aims to argue that in the age of big data, there is a need to consider the collective aspects of privacy as well and to develop new ways of calculating privacy risks and identify privacy threats that emerge.Design/methodology/approachFocusing on a collective level, the authors conducted an extensive literature review related to information privacy and concepts of social identity. They also examined numerous automated data-driven profiling techniques analyzing at the same time the involved privacy issues for groups.FindingsThis paper identifies privacy threats for collective entities that stem from data-driven profiling, and it argues that privacy-preserving mechanisms are required to protect the privacy interests of groups as entities, independently of the interests of their individual members. Moreover, this paper concludes that collective privacy threats may be different from threats for individuals when they are not members of a group.Originality/valueAlthough research evidence indicates that in the age of big data privacy as a collective issue is becoming increasingly important, the pluralist character of privacy has not yet been adequately explored. This paper contributes to filling this gap and provides new insights with regard to threats for group privacy and their impact on collective entities and society.

Journal

Information and Computer Security – Emerald Publishing

Published: Nov 7, 2019

Keywords: Profiling; Privacy implications; Big data analytics; Group privacy

There are no references for this article.