A critical review on the use (and misuse) of differential privacy in machine learning
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 …
(ML). We show that, driven by the aim of preserving the accuracy of the learned models, DP …
The long road to computational location privacy: A survey
The widespread adoption of continuously connected smartphones and tablets developed
the usage of mobile applications, among which many use location to provide geolocated …
the usage of mobile applications, among which many use location to provide geolocated …
Local differential privacy for deep learning
PCM Arachchige, P Bertok, I Khalil… - IEEE Internet of …, 2019 - ieeexplore.ieee.org
The Internet of Things (IoT) is transforming major industries, including but not limited to
healthcare, agriculture, finance, energy, and transportation. IoT platforms are continually …
healthcare, agriculture, finance, energy, and transportation. IoT platforms are continually …
A trustworthy privacy preserving framework for machine learning in industrial IoT systems
PCM Arachchige, P Bertok, I Khalil… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Industrial Internet of Things (IIoT) is revolutionizing many leading industries such as energy,
agriculture, mining, transportation, and healthcare. IIoT is a major driving force for Industry …
agriculture, mining, transportation, and healthcare. IIoT is a major driving force for Industry …
Differentially private data publishing and analysis: A survey
Differential privacy is an essential and prevalent privacy model that has been widely
explored in recent decades. This survey provides a comprehensive and structured overview …
explored in recent decades. This survey provides a comprehensive and structured overview …
PrivKV: Key-value data collection with local differential privacy
Local differential privacy (LDP), where each user perturbs her data locally before sending to
an untrusted data collector, is a new and promising technique for privacy-preserving …
an untrusted data collector, is a new and promising technique for privacy-preserving …
Privacy preserving face recognition utilizing differential privacy
Facial recognition technologies are implemented in many areas, including but not limited to,
citizen surveillance, crime control, activity monitoring, and facial expression evaluation …
citizen surveillance, crime control, activity monitoring, and facial expression evaluation …
A comprehensive survey on local differential privacy toward data statistics and analysis
T Wang, X Zhang, J Feng, X Yang - Sensors, 2020 - mdpi.com
Collecting and analyzing massive data generated from smart devices have become
increasingly pervasive in crowdsensing, which are the building blocks for data-driven …
increasingly pervasive in crowdsensing, which are the building blocks for data-driven …
Locally private graph neural networks
S Sajadmanesh, D Gatica-Perez - … of the 2021 ACM SIGSAC conference …, 2021 - dl.acm.org
Graph Neural Networks (GNNs) have demonstrated superior performance in learning node
representations for various graph inference tasks. However, learning over graph data can …
representations for various graph inference tasks. However, learning over graph data can …
[HTML][HTML] Privacy-preserving Federated Learning and its application to natural language processing
B Nagy, I Hegedűs, N Sándor, B Egedi… - Knowledge-Based …, 2023 - Elsevier
State-of-the-art edge devices are capable of not only inferring machine learning (ML)
models but also training them on the device with local data. When this local data is sensitive …
models but also training them on the device with local data. When this local data is sensitive …