131 citations · 597 across the 42 of their papers we have counts for
44 papers
Evolutionary and Coevolutionary Multi-Agent Design Choices and Dynamics
Erik Hemberg, Eric Liu, Lucille Fuller +2
We investigate two representation alternatives for the controllers of teams of cyber agents. We combine these controller representations with different evolutionary algorithms, one…
Guiding Evolutionary AutoEncoder Training with Activation-Based Pruning Operators
Steven Jorgensen, Erik Hemberg, Jamal Toutouh +1
This study explores a novel approach to neural network pruning using evolutionary computation, focusing on simultaneously pruning the encoder and decoder of an autoencoder. We intr…
Hybrid Privilege Escalation and Remote Code Execution Exploit Chains
Miguel Tulla, Andrea Vignali, Christian Colon +5
Research on exploit chains predominantly focuses on sequences with one type of exploit, e.g., either escalating privileges on a machine or executing remote code. In networks, hybri…
LLM-Supported Natural Language to Bash Translation
Finnian Westenfelder, Erik Hemberg, Miguel Tulla +3
The Bourne-Again Shell (Bash) command-line interface for Linux systems has complex syntax and requires extensive specialized knowledge. Using the natural language to Bash command (…
Evolving Code with A Large Language Model
Erik Hemberg, Stephen Moskal, Una-May O'Reilly
Algorithms that use Large Language Models (LLMs) to evolve code arrived on the Genetic Programming (GP) scene very recently. We present LLM GP, a formalized LLM-based evolutionary…
LLMs Killed the Script Kiddie: How Agents Supported by Large Language Models Change the Landscape of Network Threat Testing
Stephen Moskal, Sam Laney, Erik Hemberg +1
In this paper, we explore the potential of Large Language Models (LLMs) to reason about threats, generate information about tools, and automate cyber campaigns. We begin with a man…