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Found 10 papers, 3 papers with code
Make Split, not Hijack: Preventing Feature-Space Hijacking Attacks in Split Learning
Consequently, during both forward and backward propagation, the servers cannot reconstruct the client's raw data from the activation map.
Wildest Dreams: Reproducible Research in Privacy-preserving Neural Network Training
In addition, we present a SoK of the most recent PPML frameworks for model training and provide a comprehensive comparison in terms of the unique properties and performances on standard benchmarks.
Trustworthiness of $\mathbb{X}$ Users: A One-Class Classification Approach
In this study, we use various OCC models for $\mathbb{X}$ user classification.
GuardML: Efficient Privacy-Preserving Machine Learning Services Through Hybrid Homomorphic Encryption
Our work seeks to introduce HHE to ML by designing a PPML scheme tailored for end devices.
Love or Hate? Share or Split? Privacy-Preserving Training Using Split Learning and Homomorphic Encryption
In this setting, the client initially applies its part of the machine learning model on the raw data to generate activation maps and then sends them to the server to continue the training process.
Split Without a Leak: Reducing Privacy Leakage in Split Learning
The idea behind it is that the client encrypts the activation map (the output of the split layer between the client and the server) before sending it to the server.
Split Ways: Privacy-Preserving Training of Encrypted Data Using Split Learning
In this setting, the client initially applies its part of the machine learning model on the raw data to generate activation maps and then sends them to the server to continue the training process.
Trust and Believe -- Should We? Evaluating the Trustworthiness of Twitter Users
Hence, the identification of fake news on social media is a problem of utmost importance that has attracted the interest not only of the research community but most of the big players on both sides - such as Facebook, on the industry side, and political parties on the societal one.
Seeing and Believing: Evaluating the Trustworthiness of Twitter Users
Assigning a credibility score to a user has piqued the interest of not only the research community but also most of the big players on both sides - such as Facebook, on the side of industry, and political parties on the societal one.
SOK: Fake News Outbreak 2021: Can We Stop the Viral Spread?
Social Networks' omnipresence and ease of use has revolutionized the generation and distribution of information in today's world.
