Trident: Efficient 4pc framework for privacy preserving machine learning
Machine learning has started to be deployed in fields such as healthcare and finance, which
propelled the need for and growth of privacy-preserving machine learning (PPML). We …
propelled the need for and growth of privacy-preserving machine learning (PPML). We …
Privacy in deep learning: A survey
The ever-growing advances of deep learning in many areas including vision,
recommendation systems, natural language processing, etc., have led to the adoption of …
recommendation systems, natural language processing, etc., have led to the adoption of …
PDLM: Privacy-preserving deep learning model on cloud with multiple keys
Deep learning has aroused a lot of attention and has been used successfully in many
domains, such as accurate image recognition and medical diagnosis. Generally, the training …
domains, such as accurate image recognition and medical diagnosis. Generally, the training …
Fairfl: A fair federated learning approach to reducing demographic bias in privacy-sensitive classification models
The recent advance of the federated learning (FL) has brought new opportunities for privacy-
aware distributed machine learning (ML) applications to train a powerful ML model without …
aware distributed machine learning (ML) applications to train a powerful ML model without …
Privacy adversarial network: representation learning for mobile data privacy
S Liu, J Du, A Shrivastava, L Zhong - … of the ACM on Interactive, Mobile …, 2019 - dl.acm.org
The remarkable success of machine learning has fostered a growing number of cloud-based
intelligent services for mobile users. Such a service requires a user to send data, eg image …
intelligent services for mobile users. Such a service requires a user to send data, eg image …
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 …
Privacy-sensitive parallel split learning
J Jeon, J Kim - 2020 International Conference on Information …, 2020 - ieeexplore.ieee.org
Mobile devices and medical centers have access to rich data that is suitable for training
deep learning models. However, these highly distributed datasets are privacy sensitive …
deep learning models. However, these highly distributed datasets are privacy sensitive …
Data analytics of social media 3.0: Privacy protection perspectives for integrating social media and Internet of Things (SM-IoT) systems
With the rapid evolution of web technologies, Web 3.0 aims to expand on current and
emerging social media platforms such as Facebook, Twitter, and TikTok, and integrate …
emerging social media platforms such as Facebook, Twitter, and TikTok, and integrate …
A survey of subscription privacy on the 5G radio interface-the past, present and future
End-user privacy in mobile telephony systems is nowadays of great interest because of the
envisaged hyper-connectivity and the potential of the unprecedented services (virtual reality …
envisaged hyper-connectivity and the potential of the unprecedented services (virtual reality …
An overview of privacy in machine learning
E De Cristofaro - arXiv preprint arXiv:2005.08679, 2020 - arxiv.org
Over the past few years, providers such as Google, Microsoft, and Amazon have started to
provide customers with access to software interfaces allowing them to easily embed …
provide customers with access to software interfaces allowing them to easily embed …