| Vol-2269 urn:nbn:de:0074-2269-5 Copyright © 2018 for the individual papers by the papers' authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors.

# ALEC 2018
Adversary-Aware Learning Techniques and Trends in Cybersecurity 2018

### Proceedings of the AAAI Symposium on Adversary-Aware Learning Techniques and Trends in Cybersecurity (ALEC 2018)
co-located with the Association for the Advancement of Artificial Intelligence 2018 Fall Symposium Series (AAAI-FSS 2018)

### Arlington, Virginia, USA, October 18-20, 2018.

Edited by:

### Joseph B. Collins*
Prithviraj Dasgupta **
Ranjeev Mittu*

* Naval Research Laboratory, Information Technology Division, Washington, DC 20375, USA
** University of Nebraska, Omaha, Computer Science Department, Omaha, NE 68182, USA

## Table of Contents

- Frontmatter
- Preface

### Keynote Talks

- AI Canonical Architecture and Robust AI 1
  David Martinez
- An Optimal Control View of Adversarial Machine Learning 2
  Xiaojin Zhu

### Adversarial Data Generation and Adversarial Training

- Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus 3-10
  William Fleshman, Edward Raff, Richard Zak, Mark McLean, Charles Nicholas
- Exploring Adversarial Examples in Malware Detection 11-16
  Octavian Suciu, Scott E. Coull, Jeffrey Johns
- Gray-box Techniques for Adversarial Text Generation 17-23
  Prithviraj Dasgupta, Joseph B. Collins, Anna Buhman
- Adversarial Training on Word-Char Embedding 24-27
  Abebaw Tadesse, Joseph B. Collins

### Countering Adversarial Attacks in Cybersecurity

- Integrating Collaborative Cognitive Assistants Into Cybersecurity Operations Centers 28-35
  Steve Meckl, Gheorghe Tecuci, Dorin Marcu, Mihai Boicu
- Data and Deep Models Applied to Cyber Security Data Analysis 36-40
  Ying Zhao, Andrew Polk, Shaun Kallis, Lauren Jones, Riqui Schwamm, Tony Kendall
- Inefficiencies in Cyber-Security Exercises Life-Cycle: A Position Paper 41-43
  Muhammad Mudassar Yamin, Basel Katt

### Novel Approaches in Adversarial Artificial Intelligence

- Projecting Trouble: Light based Adversarial Attacks on Deep Learning Classifiers 44-49
  Nicole Nichols, Robert Jasper
- An Artificial Coevolutionary Framework for Adversarial AI 50-55
  Una-May O'Reilly, Erik Hemberg
- Coordination-driven Learning in Multi-agent Problem Spaces 56-58
  Sean L. Barton, Nicholas R. Waytowich, Derrik E. Asher

2018-11-07: submitted by Joseph Collins, Prithviraj Dasgupta, Ranjeev Mittu, metadata incl. bibliographic data published under Creative Commons CC0
2018-12-10: published on CEUR-WS.org |valid HTML5|