Industrial Control Systems (ICS) constitute the backbone of contemporary industrial operations, ranging from modest heating, ventilation, and air conditioning systems to expansive national power grids. Given their pivotal role in critical infrastructure, there has been a concerted effort to enhance security measures and deepen our comprehension of potential cyber threats within this domain. To address these challenges, numerous implementations of Honeypots and Honeynets intended to detect and understand attacks have been employed for ICS. This approach diverges from conventional methods by focusing on making a scalable and reconfigurable honeynet for cyber-physical systems. It will also automatically generate attacks on the honeynet to test and validate it. With the development of a scalable and reconfigurable Honeynet and automatic attack generation tools, it is also expected that the system will serve as a basis for producing datasets for training algorithms for detecting and classifying attacks in cyber-physical honeynets.

翻译：工业控制系统（ICS）构成了当代工业运营的基石，涵盖从小型供暖、通风与空调系统到大规模国家电网的各类设施。鉴于其在关键基础设施中的核心作用，该领域已投入大量精力强化安全防护措施，并深化对潜在网络威胁的理解。为应对这些挑战，多种旨在检测和理解攻击的蜜罐与蜜网实现方案已被应用于工业控制系统。本研究提出的方法有别于传统路径，其核心在于构建一种面向网络-物理系统的可扩展可重构蜜网。该蜜网还将支持自动生成攻击行为以进行测试与验证。通过开发可扩展可重构的蜜网及自动攻击生成工具，预期该系统能够为网络-物理蜜网中攻击检测与分类算法的训练数据集构建提供基础支撑。