3 citations · 3 across the 4 of their papers we have counts for
6 papers
The MAL Simulator: Cyber Operations Simulation based on Attack & Defense Graphs
Jakob Nyberg, Sandor Berglund, Andrei Buhaiu +3
We have developed the MAL Simulator, a cyber operation simulator based on the Meta Attack Language (MAL). The MAL Simulator is intended for decision-driven cyber attack and defense…
A Cyber Range Evaluation of Autonomous Network Incident Response Agents
Jakob Nyberg, Teodor Sommestad, Andrei Buhaiu +3
We test the performance of agents for automated network intrusion response in a cyber range intended for human operator training. The range implements an emulated networking enviro…
Vejde: A Framework for Inductive Deep Reinforcement Learning Based on Factor Graph Color Refinement
Jakob Nyberg, Pontus Johnson
We present and evaluate Vejde; a framework which combines data abstraction, graph neural networks and reinforcement learning to produce inductive policy functions for decision prob…
Structural Generalization in Autonomous Cyber Incident Response with Message-Passing Neural Networks and Reinforcement Learning
Jakob Nyberg, Pontus Johnson
We believe that agents for automated incident response based on machine learning need to handle changes in network structure. Computer networks are dynamic, and can naturally chang…
Training Automated Defense Strategies Using Graph-based Cyber Attack Simulations
Jakob Nyberg, Pontus Johnson
We implemented and evaluated an automated cyber defense agent. The agent takes security alerts as input and uses reinforcement learning to learn a policy for executing predefined d…
Estimating Subjective Crowd-Evaluations as an Additional Objective to Improve Natural Language Generation
Jakob Nyberg, Ramesh Manuvinakurike, Maike Paetzel-Prüsmann
Human ratings are one of the most prevalent methods to evaluate the performance of natural language processing algorithms. Similarly, it is common to measure the quality of sentenc…