Federated learning in smart cities: Privacy and security survey

R Al-Huthaifi, T Li, W Huang, J Gu, C Li - Information Sciences, 2023 - Elsevier
Over the last decade, smart cities (SC) have been developed worldwide. Implementing big
data and the internet of things improves the monitoring and integration of different …

Anonymisation models for text data: State of the art, challenges and future directions

P Lison, I Pilán, D Sánchez, M Batet… - Proceedings of the 59th …, 2021 - aclanthology.org
This position paper investigates the problem of automated text anonymisation, which is a
prerequisite for secure sharing of documents containing sensitive information about …

OBPP: An ontology-based framework for privacy-preserving in IoT-based smart city

M Gheisari, HE Najafabadi, JA Alzubi, J Gao… - Future Generation …, 2021 - Elsevier
IoT devices generate data over time, which is going to be shared with other parties to
provide high-level services. Smart City is one of its applications which aims to manage cities …

A critical review on the use (and misuse) of differential privacy in machine learning

A Blanco-Justicia, D Sánchez, J Domingo-Ferrer… - ACM Computing …, 2022 - dl.acm.org
We review the use of differential privacy (DP) for privacy protection in machine learning
(ML). We show that, driven by the aim of preserving the accuracy of the learned models, DP …

Privacy and security concerns in the smart city

BFG Fabrègue, A Bogoni - Smart Cities, 2023 - mdpi.com
This article will highlight negative personal privacy and informational security outcomes that
may arise from development programs currently pursued in smart cities. It aims to illustrate …

Privacy-preserving cloud computing on sensitive data: A survey of methods, products and challenges

J Domingo-Ferrer, O Farras, J Ribes-González… - Computer …, 2019 - Elsevier
The increasing volume of personal and sensitive data being harvested by data controllers
makes it increasingly necessary to use the cloud not just to store the data, but also to …

The long road to computational location privacy: A survey

V Primault, A Boutet, SB Mokhtar… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
The widespread adoption of continuously connected smartphones and tablets developed
the usage of mobile applications, among which many use location to provide geolocated …

[Retracted] The Rise of Cloud Computing: Data Protection, Privacy, and Open Research Challenges—A Systematic Literature Review (SLR)

J Hassan, D Shehzad, U Habib… - Computational …, 2022 - Wiley Online Library
Cloud computing is a long‐standing dream of computing as a utility, where users can store
their data remotely in the cloud to enjoy on‐demand services and high‐quality applications …

The text anonymization benchmark (tab): A dedicated corpus and evaluation framework for text anonymization

I Pilán, P Lison, L Øvrelid, A Papadopoulou… - Computational …, 2022 - direct.mit.edu
We present a novel benchmark and associated evaluation metrics for assessing the
performance of text anonymization methods. Text anonymization, defined as the task of …

Linking sensitive data

P Christen, T Ranbaduge, R Schnell - Methods and techniques for …, 2020 - Springer
Sensitive personal data are created in many application domains, and there is now an
increasing demand to share, integrate, and link such data within and across organisations in …