all AI news
Re-pseudonymization Strategies for Smart Meter Data Are Not Robust to Deep Learning Profiling Attacks
April 8, 2024, 4:42 a.m. | Ana-Maria Cretu, Miruna Rusu, Yves-Alexandre de Montjoye
cs.LG updates on arXiv.org arxiv.org
Abstract: Smart meters, devices measuring the electricity and gas consumption of a household, are currently being deployed at a fast rate throughout the world. The data they collect are extremely useful, including in the fight against climate change. However, these data and the information that can be inferred from them are highly sensitive. Re-pseudonymization, i.e., the frequent replacement of random identifiers over time, is widely used to share smart meter data while mitigating the risk of …
abstract arxiv attacks change climate climate change consumption cs.cr cs.lg data deep learning devices electricity fight however measuring profiling rate robust smart strategies type world
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
AI Research Scientist
@ Vara | Berlin, Germany and Remote
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Business Data Analyst
@ Alstom | Johannesburg, GT, ZA