… Privacy (DP) is a promising standard in the context of statistical data mining and machine
learning, … Models of smart buildings in our experiment refer to a technical survey by Iron Inc. in …

… as security of plug in electric vehicles, transactive energy and architectures and … privacy
preserving schemes that the current survey does. In addition, Cintuglu et al. [45] present a survey …

… As its advantage, FedSteg is a general framework suitable for general network structures
in privacy-preserving machine learning. Gao et al. [59] proposed a heterogeneous FTL …

… significant security and privacy-preserving V2V-charging … this study to solve the related
difficulties, are outlined. The main objective of this work is to develop a secure, privacy-preserving …

… In this study, the DRL-… preserving the privacy of data for EVCSs and reducing the training
time of LAs. The primary goal of this study is to implement the stable and privacy-preserving FRL…

… a reinforcement learning-based intelligent privacy allocation … security vulnerabilities of electric
vehicle energy infrastructure. … privacy preserving data publishing: A comprehensive survey,…

… , and combining DSO with artificial intelligence and machine learning for system optimization.
… This study aimed to create a privacy-preserving data range query (PPQ) scheme that …

… In this work, we propose deep learning models such as long … , machine learning, and deep
learning. However, there is a lack of literature specifically focusing on electric vehicle study …

… a tree-based privacy-preserving context-based deep learning EV … Privacy-preserving
context-based electric vehicle dispatching for energy scheduling in microgrids: An online learning …

… In recent years, privacy preservation methodologies have … Effectively, in the present paper,
we aim to study various literature … an advanced Deep Learning model can solve this issue. …