Shah Chintan, Nachand Douglas, Wald Christoph, Chen Po-Hao
Associate Staff, Section of Neuroradiology and Section of Imaging Informatics, Safety, Improvement, Quality and Experience Officer-Neuroradiology, Department of Radiology, Imaging Institute, Cleveland Clinic, Cleveland, Ohio.
Staff, Section of Abdominal Imaging and Section of Imaging Informatics, Cleveland Clinic, Cleveland, Ohio.
J Am Coll Radiol. 2023 Sep;20(9):828-835. doi: 10.1016/j.jacr.2023.06.023. Epub 2023 Jul 22.
Artificial intelligence (AI)-based solutions are increasingly being incorporated into radiology workflows. Implementation of AI comes along with cybersecurity risks and challenges that practices should be aware of and mitigate for a successful and secure deployment. In this article, these cybersecurity issues are examined through the lens of the "CIA" triad framework-confidentiality, integrity, and availability. We discuss the implications of implementation configurations and development approaches on data security and confidentiality and the potential impact that the insertion of AI can have on the truthfulness of data, access to data, and the cybersecurity attack surface. Finally, we provide a checklist to address important security considerations before deployment of an AI application, and discuss future advances in AI addressing some of these security concerns.
基于人工智能(AI)的解决方案越来越多地被纳入放射学工作流程。人工智能的实施伴随着网络安全风险和挑战,医疗机构应了解并减轻这些风险,以实现成功且安全的部署。在本文中,我们通过“CIA”三元组框架(保密性、完整性和可用性)来审视这些网络安全问题。我们讨论了实施配置和开发方法对数据安全和保密性的影响,以及人工智能的引入可能对数据真实性、数据访问和网络安全攻击面产生的潜在影响。最后,我们提供了一份清单,以在部署人工智能应用程序之前解决重要的安全考虑因素,并讨论人工智能在解决其中一些安全问题方面的未来进展。