Accepted Papers

Generative Adversarial Attacks Against Intrusion Detection System Using Active Learning
Dule Shu1, Nandi Leslie2, Charles Kamhoua2, and Conrad Tucker1
1 Carnegie Mellon University, USA
2 Army Research Laboratory, USA
Data Augmentation with Conditional GAN for Automatic Modulation Classification
Mansi Patel1, Xuyu Wang1, and Shiwen Mao2
1 California State University, USA
2 Auburn University, USA
Encrypted Rich-data Steganography using Generative Adversarial Networks
Dule Shu1, Weilin Cong2, Jiaming Chai2, and Conrad Tucker1
1 Carnegie Mellon University, USA
2 Pennsylvania State University, USA
A Network Security Classifier Defense: Against Adversarial Machine Learning Attacks
Michael J. De Lucia1 and Chase Cotton2
1 Army Research Laboratory, USA
2 University of Delaware, USA
Machine Learning-Driven Intrusion Detection for Contiki-NG-Based IoT Networks Exposed to NSL-KDD Dataset
Jinxin Liu1, Burak Kantarci1, and Carlisle Adams1
1 University of Ottawa, Canada
Algorithm Selection Framework for Cyber Attack Detection
Marc Chale1, Nathaniel Bastian2, and Jeffery D Weir1
1 Air Force Institute of Technology, USA
2 Army Cyber Institute, USA
Detecting Acoustic BackDoor Transmission of Inaudible Messages Using Deep Learning
Silvija Kokalj-Filipovic1, Morriel Kasher2, Michael Zhao2, and Predrag Spasojevic2
1 Perspecta Labs, Inc., USA
2 Rutgers University, USA
Over-the-Air Membership Inference Attacks as Privacy Threats for Deep Learning-based Wireless Signal Classifiers
Yi Shi1, Kemal Davaslioglu1, and Yalin Sagduyu1
1 Intelligent Automation, Inc., USA
Generalized Wireless Adversarial Deep Learning
Francesco Restuccia1, Salvatore D'Oro1, Amani Alshawabka1, Bruno Costa Rendon1, Kaushik Chowdhury1, Stratis Ioannidis1, and Tommaso Melodia1
1 Northeastern University, USA
Adversarial machine learning based partial-model attack in IoT
Zhengping Luo1, Shangqing Zhao1, Zhuo Lu1, Yalin E. Sagduyu2, and Jie Xu3
1 University of South Florida, USA
2 Intelligent Automation, Inc., USA
3 University of Miami, USA
Investigating a Spectral Deception Loss Metric for Training Machine Learning-based Evasion Attacks
Matthew DelVecchio1, William C. Headley1, and Vanessa Arndorfer1
1 Virginia Tech Hume Center, USA
Deep Learning Based Wiretap Coding via Mutual Information Estimation
Rick Fritschek1, Rafael F. Schaefer2, and Gerhard Wunder1
1 Freie Universität Berlin, Germany
2 Technische Universität Berlin, Germany
Wideband Spectral Monitoring Using Deep Learning
Horacio Franco1, Chris Cobo-Kroenke1, Stephanie Welch1, and Martin Graciarena1
1 SRI International, USA
Open Set Recognition through Unsupervised and Class-Distance Learning
Andrew Draganov1, Carter Brown1, Enrico Mattei1, Cass Dalton1, and Jaspreet Ranjit2
1 Expedition Technology, Inc., USA
2 University of Virginia, USA