A comprehensive survey of privacy-preserving federated learning: A taxonomy, review, and future directions
The past four years have witnessed the rapid development of federated learning (FL).
However, new privacy concerns have also emerged during the aggregation of the …
However, new privacy concerns have also emerged during the aggregation of the …
Machine learning techniques for hate speech classification of twitter data: State-of-the-art, future challenges and research directions
Twitter is a microblogging tool that allow the creation of big data through short digital
contents. This study provides a survey of machine learning techniques for hate speech …
contents. This study provides a survey of machine learning techniques for hate speech …
Confronting abusive language online: A survey from the ethical and human rights perspective
The pervasiveness of abusive content on the internet can lead to severe psychological and
physical harm. Significant effort in Natural Language Processing (NLP) research has been …
physical harm. Significant effort in Natural Language Processing (NLP) research has been …
Towards security threats of deep learning systems: A survey
Deep learning has gained tremendous success and great popularity in the past few years.
However, deep learning systems are suffering several inherent weaknesses, which can …
However, deep learning systems are suffering several inherent weaknesses, which can …
Privft: Private and fast text classification with homomorphic encryption
We present an efficient and non-interactive method for Text Classification while preserving
the privacy of the content using Fully Homomorphic Encryption (FHE). Our solution (named …
the privacy of the content using Fully Homomorphic Encryption (FHE). Our solution (named …
High performance logistic regression for privacy-preserving genome analysis
M De Cock, R Dowsley, ACA Nascimento… - BMC Medical …, 2021 - Springer
Background In biomedical applications, valuable data is often split between owners who
cannot openly share the data because of privacy regulations and concerns. Training …
cannot openly share the data because of privacy regulations and concerns. Training …
AI at the edge: Blockchain-empowered secure multiparty learning with heterogeneous models
Edge computing, an emerging computing paradigm pushing data computing and storing to
network edges, enables many applications that require high computing complexity …
network edges, enables many applications that require high computing complexity …
Sok: Content moderation for end-to-end encryption
S Scheffler, J Mayer - arXiv preprint arXiv:2303.03979, 2023 - arxiv.org
Popular messaging applications now enable end-to-end-encryption (E2EE) by default, and
E2EE data storage is becoming common. These important advances for security and privacy …
E2EE data storage is becoming common. These important advances for security and privacy …
“All apps do this”: Comparing Privacy Concerns Towards Privacy Tools and Non-Privacy Tools for Social Media Content
Users report that they have regretted accidentally sharing personal information on social
media. There have been proposals to help protect the privacy of these users, by providing …
media. There have been proposals to help protect the privacy of these users, by providing …