08:30-09:00 breakfast

09:00-09:45 Keynote - Maya Gupta, Principle Scientist, Google

Maya Gupta, “Do You Know What Your ML Is Doing?”

09:45-10:00 coffee

10:00-11:30 Session 4

1. Matthew Berninger, “APTinder: An optimized approach for finding that perfect APT match”

2. Awalin Nabila Sopan, “Interpretation of Threat Prediction Model for SOC Analysts”

3. Cody Wild, “Some Mistakes are More Mistaken Than Others: Using Cost-Matrix Clustering to Address Misclassification Cost Asymmetries in Website Content Classification”

11:30-13:00 lunch

13:00-14:30 Session 5

1. Bronwyn Woods, “Point process modeling of temporal patterns in user authentication behavior”

2. Frances Zlotnick, “Using Anomaly Detection on User Demographic Distributions to Identify Fake Account Bursts”

3. Richard Harang, “Estimating uncertainty for binary classifiers”

14:30-15:00 coffee

15:00-16:30 Session 6

1. Bobby Filar, “TreeHuggr: Discovering where tree-based classifiers are vulnerable to adversarial attack”

2. Malachi Jones, “Automated in-memory malware/rootkit detection via binary analysis and machine learning”

3. Lindsey Lack, “Improved Multi-Stage Classification for Information Security Applications”

16:30-16:45 Closing remarks

08:30-9:00 breakfast

09:00-09:15 CAMLIS 2018 Welcome and Introduction

09:15-10:00 Keynote - Alexander Kott, Chief Scientist, Army Research Laboratory

Alexander Kott, “Bonware to the Rescue: the Future Autonomous Cyber Defense Agents”

10:00-10:15 coffee

10:15-11:45 Session 1

1. Jay Yang, “Anticipatory Cyber Defense via Predictive Analytics, Machines Learning and Simulation”

2. Bayan Bruss, “Worm2Vec: Embedding Malicious Code for Efficient Clustering & Classification”

3. Rebecca Bilbro, “Inferring Model Families from Deployed Black Boxes”

11:45-13:00 lunch

13:00-14:30 Session 2

1. Kyle Gwinnup, “Serverless Data Processing Architecture for Binary Analysis”

2. Ryan Kovar, “Datasets for the Everyman”

3. Brian Genz, “Labeling Red: Harvesting Labeled Data from Adversary Simulations”

14:30-15:00 coffee

15:00-17:00 Session 3

1. Scott Coull, “Activation Analysis of a Byte-based Deep Neural Network for Malware Classification”

2. Hyrum Anderson, “A feature presentation: semi-supervised learning of file representations”

3. David Krisiloff, “Measure Twice, Quarantine Once: A Tale of Malware Labeling over Time”

4. Nahid Farhady, “An Effective Framework for Malware Detection and Classification using Feature Prioritization”

17:00-18:30 CAMLIS 2018 happy hour