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