Privacy-Preserving Identifiers for IoT: A Systematic Literature Review

被引:11
作者
Akil, Mahdi [1 ]
Islami, Lejla [1 ]
Fischer-Hubner, Simone [1 ]
Martucci, Leonardo A. [1 ]
Zuccato, Albin [2 ]
机构
[1] Karlstad Univ, Comp Sci Dept, S-65188 Karlstad, Sweden
[2] ICA Grp AB, IT Secur & IT Privacy, S-17193 Solna, Sweden
来源
IEEE ACCESS | 2020年 / 8卷
关键词
Databases; Bibliographies; Privacy; Internet of Things; Computer architecture; Libraries; identity; pseudonym; anonymous credential; the IoT; systematic literature review; AUTHENTICATION; IDENTITY; INTERNET;
D O I
10.1109/ACCESS.2020.3023659
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Internet of Things (IoT) paves the way for smart applications such as in E-health, E-homes, transportation, or energy production. However, IoT technologies also pose privacy challenges for their users, as they allow the tracking and monitoring of the users' behavior and context. The EU General Data Protection Regulation (GDPR) mandates data controller to follow a data protection by design and default approach by implementing for instance pseudonymity for achieving data minimisation. This paper provides a systematic literature review for answering the question of what types of privacy-preserving identifiers are proposed by the literature in IoT environments for implementing pseudonymity. It contributes with classifications and analyses of IoT environments for which privacy-preserving identifiers have been proposed and of the pseudonym types and underlying identity management architectures used. Moreover, it discusses trends and gaps in regard to addressing privacy trade-offs.
引用
收藏
页码:168470 / 168485
页数:16
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