20 citations · 40 across the 8 of their papers we have counts for
14 papers · 1 filter
Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study
Yuchen Lei, Yuexin Xiang, Qin Wang +4
Cryptocurrencies are widely used, yet current methods for analyzing transactions often rely on opaque, black-box models. While these models may achieve high performance, their outp…
SePEnTra: A secure and privacy-preserving energy trading mechanisms in transactive energy market
Rumpa Dasgupta, Amin Sakzad, Carsten Rudolph +1
In this paper, we design and present a novel model called SePEnTra to ensure the security and privacy of energy data while sharing with other entities during energy trading to dete…
Privacy-Preserving Training of Tree Ensembles over Continuous Data
Samuel Adams, Chaitali Choudhary, Martine De Cock +5
Most existing Secure Multi-Party Computation (MPC) protocols for privacy-preserving training of decision trees over distributed data assume that the features are categorical. In re…
Privacy-Preserving Feature Selection with Secure Multiparty Computation
Xiling Li, Rafael Dowsley, Martine De Cock
Existing work on privacy-preserving machine learning with Secure Multiparty Computation (MPC) is almost exclusively focused on model training and on inference with trained models,…
Privacy-Preserving Video Classification with Convolutional Neural Networks
Sikha Pentyala, Rafael Dowsley, Martine De Cock
Many video classification applications require access to personal data, thereby posing an invasive security risk to the users' privacy. We propose a privacy-preserving implementati…
Fast Privacy-Preserving Text Classification based on Secure Multiparty Computation
Amanda Resende, Davis Railsback, Rafael Dowsley +2
We propose a privacy-preserving Naive Bayes classifier and apply it to the problem of private text classification. In this setting, a party (Alice) holds a text message, while anot…