… 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 …

… 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…

… and privacy, threats and vulnerabilities, communication, and computation costs. In this
survey, we focus on cryptographic techniques proposed to achieve authentication, privacy, and …

… LDP researches and the privacy preservation in IoV. The originality of this survey is that it is
the … is that users locally perturb parameter updates of machine learning on their vehicle data …

… Recent trends in Plug-in Electric Vehicles (PEV) have also increased the potential for …
However, Reinforcement Learning do not estimate the actual input/output characteristic but only …

… [5] proposed the approach using deep learning and AI methods to help the analysis of … the
user, we will compute the privacy level of the original negative survey method as well as the …

… the integrity of machine learning approaches and data sharing privacy, respectively. In [27], …
Xiao, “Privacy preservation for V2G networks in smart grid: A survey,” Comput. Commun., vol…

… We focus on common means of privacy preservation for ML and privacy protection via ML.
We can use technology control such as DP and homomorphic encryption to protect …

… detailed survey on existing data fusion methods applied in three main IoT application domains
in Section 3. Based on our literature survey, … Machine learning is mainly divided into three …

… In general, one can enhance PPFL by constructing PPAgg protocols widely adopted in
standard distributed PrivacyPreserving Machine Learning (PPML). However, compared to PPML, …