Article ID Journal Published Year Pages File Type
6883927 Computers & Security 2018 42 Pages PDF
Abstract
In this paper we study the effect of Advanced Metering Infrastructure (AMI) dataset characteristics on privacy preserving solutions previously proposed in the literature. We focus on common characteristics (data granularity, retention time and use of pseudonyms) and we study their effect on two privacy violations: de-anonymization and de-pseudonymization. In order to better understand their effect, we study the capabilities of the adversary through its modeling and description by a probabilistic framework. We perform evaluations on a large dataset collected from a real AMI environment. Our results show that simple changes in the data collection procedure can help mitigate the outcome of these privacy violations.
Related Topics
Physical Sciences and Engineering Computer Science Computer Networks and Communications
Authors
, , ,