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WiseML@WiSec 2020: Linz, Austria
- René Mayrhofer, Michael Roland
:
Proceedings of the 2nd ACM Workshop on Wireless Security and Machine Learning, WiseML@WiSec 2020, Linz, Austria, July 13, 2020. ACM 2020, ISBN 978-1-4503-8007-2 - Dule Shu, Nandi O. Leslie, Charles A. Kamhoua, Conrad S. Tucker:
Generative adversarial attacks against intrusion detection systems using active learning. 1-6 - Andrew Draganov, Carter Brown, Enrico Mattei, Cass Dalton, Jaspreet Ranjit:
Open set recognition through unsupervised and class-distance learning. 7-12 - Zhengping Luo
Adversarial machine learning based partial-model attack in IoT. 13-18 - Horacio Franco, Chris Cobo-Kroenke, Stephanie Welch, Martin Graciarena:
Wideband spectral monitoring using deep learning. 19-24 - Jinxin Liu
Machine learning-driven intrusion detection for Contiki-NG-based IoT networks exposed to NSL-KDD dataset. 25-30 - Mansi Patel, Xuyu Wang
Data augmentation with conditional GAN for automatic modulation classification. 31-36 - Marc Chalé, Nathaniel D. Bastian, Jeffery Weir:
Algorithm selection framework for cyber attack detection. 37-42 - Matthew DelVecchio, Vanessa Arndorfer, William C. Headley:
Investigating a spectral deception loss metric for training machine learning-based evasion attacks. 43-48 - Francesco Restuccia, Salvatore D'Oro
Generalized wireless adversarial deep learning. 49-54 - Dule Shu, Weilin Cong, Jiaming Chai, Conrad S. Tucker:
Encrypted rich-data steganography using generative adversarial networks. 55-60 - Yi Shi
Over-the-air membership inference attacks as privacy threats for deep learning-based wireless signal classifiers. 61-66 - Michael J. De Lucia, Chase Cotton:
A network security classifier defense: against adversarial machine learning attacks. 67-73 - Rick Fritschek, Rafael F. Schaefer
Deep learning based wiretap coding via mutual information estimation. 74-79 - Silvija Kokalj-Filipovic, Morriel Kasher
Detecting acoustic backdoor transmission of inaudible messages using deep learning. 80-85
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