Motivation for Model‐driven Penetration Testing
Abdul Rahman, Christopher Redino, Dhruv Nandakumar, Tyler Cody, Sachin Shetty, Dan Radke · 2024
This chapter provides a motivation for reinforcement learning (RL)-based automation of penetration testing. Critiques of existing methods are given. Recent research into automating penetration testing with RL is reviewed. And a long-term research direction for RL-based automated penetration testing is given in terms of “whole campaign emulation,” a challenge problem and concept for operations.