Informing Autonomous Deception Systems with Cyber Expert Performance Data

no code implementations • 31 Aug 2021 • Maxine Major, Brian Souza, Joseph DiVita, Kimberly Ferguson-Walter

The performance of artificial intelligence (AI) algorithms in practice depends on the realism and correctness of the data, models, and feedback (labels or rewards) provided to the algorithm.

reinforcement-learning Reinforcement Learning (RL)

Incorporating Deception into CyberBattleSim for Autonomous Defense

no code implementations • 31 Aug 2021 • Erich Walter, Kimberly Ferguson-Walter, Ahmad Ridley

Deceptive elements, including honeypots and decoys, were incorporated into the Microsoft CyberBattleSim experimentation and research platform.

CyberBattleSim reinforcement-learning +1

Proceedings of the 1st International Workshop on Adaptive Cyber Defense

no code implementations • 19 Aug 2021 • Damian Marriott, Kimberly Ferguson-Walter, Sunny Fugate, Marco Carvalho

This workshop was organized to share research that explores unique applications of Artificial Intelligence (AI) and Machine Learning (ML) as foundational capabilities for the pursuit of adaptive cyber defense.

Proceedings - AI/ML for Cybersecurity: Challenges, Solutions, and Novel Ideas at SIAM Data Mining 2021

no code implementations • 27 Apr 2021 • John Emanuello, Kimberly Ferguson-Walter, Erik Hemberg, Una-May O Reilly, Ahmad Ridley, Dennis Ross, Diane Staheli, William Streilein

Malicious cyber activity is ubiquitous and its harmful effects have dramatic and often irreversible impacts on society.