联邦网络安全测试床即服务（FCTaaS）：一种联邦化网络安全测试床的框架
Federated Cybersecurity Testbed as a Service (FCTaaS): A framework to federate cybersecurity testbeds
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中文总结 AI 辅助
针对技术变革带来的网络安全研究挑战，提出FCTaaS框架，通过VPN连接异构网络安全测试床，支持跨地域协同实验，经案例研究评估，该框架能有效实现跨测试床实验，在资源利用和延迟控制上表现良好。
中文摘要 AI 辅助
快速的技术变革通过自动驾驶汽车和智能制造等新兴领域重塑社会，在系统设计、运行、安全和培训方面带来新研究挑战。研究人员常依赖测试床，但创新步伐使单个测试床难以保持代表性且成本高，且访问受限。本文提出FCTaaS框架，通过VPN连接独立管理的测试床，支持远程发现、实验设计和协同实验。通过三个案例研究评估，结果表明FCTaaS能实现有效跨测试床实验，在资源密集攻击场景下，网络利用率限制在49%，开销仅1%，延迟在5.63毫秒到147毫秒之间。
英文摘要
Rapid technological change is reshaping society through emerging domains such as autonomous vehicles and smart manufacturing, creating new research challenges in system design, operation, security, and training. Researchers often rely on testbeds to reproduce experimental scenarios, collect and analyze data, observe system behavior, and evaluate proposed solutions. However, the fast pace of innovation makes it difficult and costly for individual testbeds to remain representative of state-of-the-art systems, as doing so requires frequent upgrades and new capabilities. Moreover, access to specialized testbeds is often limited to a small group of researchers, leaving valuable infrastructure underutilized during its operational lifetime. This paper presents FCTaaS, a Federated Cybersecurity Testbed as a Service framework that enables heterogeneous cybersecurity testbeds to participate in a single experiment across geographical boundaries. By connecting independently managed testbeds through a Virtual Private Network (VPN), FCTaaS supports remote testbed discovery, experiment design, and coordinated experimentation. We evaluate FCTaaS across three case studies involving denial-of-service scenarios on smart infrastructure and intrusion detection and prevention workflows using a Suricata-based IDS/IPS testbed. The results show that FCTaaS enables effective cross-testbed experimentation while preserving visibility into attack traffic, IDS alerts, and detection-system resource stress. Even under resource-intensive attack scenarios, FCTaaS achieves limiting network utilization of 49%, introduces only 1% overhead, and supports latency ranging from 5.63 ms between local nodes to 147 ms between geographically dispersed nodes.
