Realistic and Lightweight Cyber Agent Training Environment using Network Emulation in Mininet

被引:0
作者
Yeh, Chih-Ting [1 ]
Neema, Himanshu [1 ]
Balasubramanian, Daniel [1 ]
机构
[1] Vanderbilt Univ, Nashville, TN 37232 USA
来源
PROCEEDINGS THE 6TH WORKSHOP ON DESIGN AUTOMATION FOR CPS AND IOT, DESTION 2024 | 2024年
关键词
Autonomous Cyber Defense; Cybersecurity; Network Emulation; Reinforcement Learning;
D O I
10.1109/DESTION62938.2024.00011
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this work, we enhance the CybORG [1] framework to replace its abstract network simulation with lightweight emulation using Mininet [2]. CybORG's abstract simulation provides efficiency for training cyber agents, but its low-fidelity lacks realism needed for training real-world cyber agents. On the other hand, full cloud-based network emulation or live subnets both provide high-fidelity but require additional resources. Our approach is to strike a balance between the two by using the lightweight emulation capabilities of Mininet, thereby simultaneously emphasizing efficiency, cost-effectiveness, and realism. The proposed demonstration highlights the advantages of Mininet-based emulation and its use for cyber-agent training and rapid validation with minimal resource requirements. In addition, our environment enables the collection of network utilization metrics that can further improve cyber-agent training. This work not only broadens the applicability of CybORG for cybersecurity research, but also provides a more realistic, scalable, and cost-efficient environment for cyber agent training.
引用
收藏
页码:28 / 29
页数:2
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