This paper presents an automated penetration testing framework that employs deep reinforcement learning to automate the penetration testing process. We plan to ...

AutoPentest-DRL is an automated penetration testing framework based on Deep Reinforcement Learning (DRL) techniques.

Aug 21, 2023 · Deep reinforcement learning leverages deep neural networks as function approximators to represent the agent's policy or value function. These ...

In 2020, Hu et al. [9] used the MulVAL tool and reinforcement learning algorithms to automate network penetration testing.

This paper introduces RLAPT, a novel DRL approach that directly overcomes these challenges and enables intelligent automation of the PT process with precise ...

In [7], a deep reinforcement learning model is proposed to apply to the automated testing problem. However, to increase the performance of the deep ...

May 15, 2019 · This project investigated the application of model-free Reinforcement Learning (RL) to automated pentesting.

Duration: 35:13
Posted: Oct 16, 2021

This paper presents an automated penetration testing framework that employs deep reinforcement learning to automate the penetration testing process.

A PPO agent leveraging reinforcement learning performs Penetration Testing in a simulated computer network environment.