… [83] to detect the adversary in IoT enable environments. The … data collection in smart healthcare
system using raspberry-pi, in… Jain, Machine learning based network vulnerability analysis …

… adversarial attacks in the cyberspace and may become the weakest part of the defense system.
… Practical evasion of a learning-based classifier: A case study. In: Proceedings of the 35th …

… ], and generative adversarial networks[126], these techniques have also been applied to
the field of gesture recognition. In [127] a transfer learning based convolutional neural network …

… in machine learning, and analyzes the causes and attack methods of data poisoning attacks,
adversary attacks, data stealing attacks, and querying attacks. Furthermore, the existing …

… In this paper, we proposed the conceptual model for blockchain-enabled federated learning
based on a comprehensive review of related literatures, and discussed the key techniques, …

… A machine learning-based framework to identify type 2 diabetes through electronic
health records. International Journal of Medical Informatics, 2017, 97: 120−127 doi: 10.1016/j.ijmedinf…

… Support vector machines under adversarial label contamina… attack in federated learning
using generative adversarial nets[… in federated learning using generative adversarial network[C]/…

… financial data, health care, etc.). How to prot first introduces the concept of machine learning
privacy threats encountered in machine learning … Table 1 Adversarial model of privacy attack …

… 为此,提出了一种基于人在回路(human-in-the-loop,HITL)的纵向联邦学习解 释方法(explainable
vertical federated learning based on human-in-the-loop,XVFL-HITL),通过构建分布式HITL …

… Deep neural learning based distributed predictive control for offshore wind farm using high-…
Cyber-physical healthcare system with blood test module on broadcast television network for …