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

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