… attack is taken place at the 6LoWPAN layer, where the attacker makes a tunnel between two
nodes that are connected ||51|. The Side channel security attack … , Machine learning based …

… and challenges of research on adversarial machine learning … Practical evasion of a
learning-based classifier: A case study… membership inference attacks and defenses on machine …

… we propose a general property inference attack initiated by the … the vertical federated learning
during the training process can … challenge of distributed deep learning privacy and security …

… issues that happen in the training, testing/inference phase of machine learning, which include
privacy leaking and attacks of … learning based on hierarchical extreme learning machine[J]. …

… ever-changing attack methods is a challenge faced by face … methods, such as deep-learning-based
methods and feature-… reducing much training time and inference time. Compared …

… holistic view of security issues for deep convolutional neural … threat models for the adversarial
attack and defense arms race. … black-box attacks to deep neural networks without training …

… some challenges that need further study. On one hand, the “generalization” enables a neural
network to accurately infer a … Herein, we explore another example of a deep learning based …

… Besides we also discuss some open issues of this research area… , voice assistant attacks,
and voice assistant protection touch in … In [127] a transfer learning based convolutional neural …

… This article mainly explores the security and privacy challenges … understanding of the potential
attacks. Second,three types of … Demysti⁃ fying membership inference attacks in machine …

… challenges in this research area are discussed. Key words: machine learning; security and
privacy; attack … Membership inference attacks against machine learning models. In: Proc. of …