CAMLIS 2022
Conference on Applied Machine Learning in Information Security

Table of Contents

• Inroads into Autonomous Network Defence using Explained Reinforcement Learning 1-19
  Myles Foley, Mia Wang, Zoe M, Chris Hicks, Vasilios Mavroudis
• Learning to Embed Byte Sequences with Convolutional Autoencoders 20-29
  Doug Sibley
• Firenze: Model Evaluation Using Weak Signals 30-51
  Bhavna Soman, Ali Torkamani, Michael J. Morais, Jeffrey Bickford, Baris Coskun
• Network Security Modelling with Distributional Data 52-64
  Subhabrata Majumdar, Ganesh Subramaniam
• Efficient Malware Analysis Using Metric Embeddings 65-80
  Ethan M. Rudd, David Krisiloff, Daniel Olszewski, Edward Raff, James Holt
• Minimizing Compute Costs: When Should We Run More Expensive Malware Analysis? 81-99
  Andre T. Nguyen, Richard Zak, Luke E. Richards, Maya Fuchs, Fred Lu, Robert Brandon, Gary Lopez Munoz, Edward Raff, Charles Nicholas, James Holt
• Temporal Attack Detection in Multimodal Cyber-Physical Systems with Sticky HDP-HMM 100-112
  Andrew E. Hong, Peter P. Malinovsky, Suresh Damodaran
• Threat Class Predictor: An explainable framework for predicting vulnerability threat using topic and trend modeling 113-124
  François Labrèche, Serge-Olivier Paquette