A review of homomorphic encryption for privacy-preserving biometrics
The advancement of biometric technology has facilitated wide applications of biometrics in
law enforcement, border control, healthcare and financial identification and verification …
law enforcement, border control, healthcare and financial identification and verification …
Privacy–enhancing face biometrics: A comprehensive survey
Biometric recognition technology has made significant advances over the last decade and is
now used across a number of services and applications. However, this widespread …
now used across a number of services and applications. However, this widespread …
[HTML][HTML] An efficient CNN based epileptic seizures detection framework using encrypted EEG signals for secure telemedicine applications
Recently, the rapid development of Artificial Intelligence (AI) applied in the Medical Internet
of Things (MIoT) for the diagnosis of diseases such as epilepsy based on the investigation of …
of Things (MIoT) for the diagnosis of diseases such as epilepsy based on the investigation of …
A survey of deep learning architectures for privacy-preserving machine learning with fully homomorphic encryption
Outsourced computation for neural networks allows users access to state-of-the-art models
without investing in specialized hardware and know-how. The problem is that the users lose …
without investing in specialized hardware and know-how. The problem is that the users lose …
Privacy-Preserving Data-Driven Learning Models for Emerging Communication Networks: A Comprehensive Survey
With the proliferation of Beyond 5G (B5G) communication systems and heterogeneous
networks, mobile broadband users are generating massive volumes of data that undergo …
networks, mobile broadband users are generating massive volumes of data that undergo …
Privacy-preserving deep learning with homomorphic encryption: An introduction
A Falcetta, M Roveri - IEEE Computational Intelligence …, 2022 - ieeexplore.ieee.org
Privacy-preserving deep learning with homomorphic encryption (HE) is a novel and
promising research area aimed at designing deep learning solutions that operate while …
promising research area aimed at designing deep learning solutions that operate while …
Privacy‐preserving data mining and machine learning in healthcare: Applications, challenges, and solutions
VS Naresh, M Thamarai - Wiley Interdisciplinary Reviews: Data …, 2023 - Wiley Online Library
Data mining (DM) and machine learning (ML) applications in medical diagnostic systems
are budding. Data privacy is essential in these systems as healthcare data are highly …
are budding. Data privacy is essential in these systems as healthcare data are highly …
Advances and vulnerabilities in modern cryptographic techniques: A comprehensive survey on cybersecurity in the domain of machine/deep learning and quantum …
In the contemporary landscape, where a huge amount of data plays a vital role, the
importance of strong and robust cybersecurity measures has become increasingly …
importance of strong and robust cybersecurity measures has become increasingly …
{SoK}: All You Need to Know About {On-Device}{ML} Model Extraction-The Gap Between Research and Practice
On-device ML is increasingly used in different applications. It brings convenience to offline
tasks and avoids sending user-private data through the network. On-device ML models are …
tasks and avoids sending user-private data through the network. On-device ML models are …
Incorporating privacy by design principles in the modification of AI systems in preventing breaches across multiple environments, including public cloud, private cloud …
SU Okon, O Olateju, OS Ogungbemi… - … Public Cloud, Private …, 2024 - papers.ssrn.com
The rapid integration of artificial intelligence (AI) across various sectors has significantly
amplified privacy concerns, particularly with the growing reliance on cloud environments …
amplified privacy concerns, particularly with the growing reliance on cloud environments …