CubeSats have revolutionized access to space by providing affordable and accessible platforms for research and education. However, their reliance on Commercial Off-The-Shelf (COTS) components and open-source software has introduced significant cybersecurity vulnerabilities. Ensuring the cybersecurity of CubeSats is vital as they play increasingly important roles in space missions. Traditional security measures, such as intrusion detection systems (IDS), are impractical for CubeSats due to resource constraints and unique operational environments. This paper provides an in-depth review of current cybersecurity practices for CubeSats, highlighting limitations and identifying gaps in existing methods. Additionally, it explores non-cyber anomaly detection techniques that offer insights into adaptable algorithms and deployment strategies suitable for CubeSat constraints. Open research problems are identified, including the need for resource-efficient intrusion detection mechanisms, evaluation of IDS solutions under realistic mission scenarios, development of autonomous response systems, and creation of cybersecurity frameworks. The addition of TinyML into CubeSat systems is explored as a promising solution to address these challenges, offering resource-efficient, real-time intrusion detection capabilities. Future research directions are proposed, such as integrating cybersecurity with health monitoring systems, and fostering collaboration between cybersecurity researchers and space domain experts.

翻译：立方星通过提供低成本、易获取的研究与教育平台，彻底改变了太空探索的途径。然而，其对商用现成（COTS）组件和开源软件的依赖引入了重大网络安全漏洞。确保立方星的网络安全至关重要，因为它们在太空任务中扮演着日益重要的角色。受限于资源约束和独特的运行环境，传统的安全措施（如入侵检测系统IDS）在立方星上并不适用。本文深入综述了当前立方星的网络安全实践，重点阐述了现有方法的局限性并识别了其中的空白。此外，文章还探讨了非网络异常检测技术，这些技术为适应立方星约束的可适配算法与部署策略提供了启示。本文识别了开放研究问题，包括对资源高效型入侵检测机制的需求、在真实任务场景下评估IDS解决方案、开发自主响应系统以及构建网络安全框架。将TinyML融入立方星系统作为应对这些挑战的可行方案进行了探索，该方案提供了资源高效、实时的入侵检测能力。本文还提出了未来研究方向，例如将网络安全与健康监测系统整合，以及促进网络安全研究人员与太空领域专家的协作。