使用GDELT绘制医疗保健中的网络威胁格局:一种多方法方法
Anna Piazza1, Srinidhi Vasudevan1
1Anna Piazza, PhD, is a Senior Lecturer in Economic Sociology, and Srinidhi Vasudevan, PhD, is a Senior Lecturer in Business Management; both in the School Business, Operations and Strategy, University of Greenwich, London, United Kingdom.
Health security
|May 16, 2025
概括
从2017年到2023年,对医院的网络攻击激增,网络恐怖主义和勒索软件等关键威胁正在增加. 了解这些不断变化的网络威胁对于国家基础设施网络安全和政策制定至关重要.
科学领域:
- 网络安全 网络安全
- 医疗信息学 医疗信息学
- 网络安全 网络安全
背景情况:
- 关键的国家基础设施,包括医院,面临着来自网络攻击的重大威胁.
- 像WannaCry勒索软件攻击这样的事件凸显了对个人安全和福祉的严重影响.
- 了解不断变化的网络威胁对于在医疗保健领域制定有效的预防措施至关重要.
研究的目的:
- 确定针对医院的网络攻击的流行程度和类型.
- 分析2017年至2023年医疗保健部门网络威胁的演变.
- 通过分析新闻报道,揭示网络攻击演变中的有意义模式.
主要方法:
- 这是一种多方法方法,结合了社交网络分析,自然语言处理和机器学习.
- 使用来自全球事件,语言和音调数据库 (GDELT) 的数据.
- 分析新闻媒体报道的新出现的网络攻击之间的关系.
主要成果:
- 2017年至2023年间,对医院的网络攻击大幅增加.
- 医院越来越容易受到关键攻击,包括网络恐怖主义,国家赞助的活动,先进的持续威胁和分布式拒绝服务 (DDoS).
- 通过数据分析,确定了网络攻击演变中的有意义模式.
结论:
- 使用多方法方法绘制实时数据可以提高对网络威胁格局的理解.
- 这种理解对于为关键国家基础设施开发必要的网络防御至关重要.
- 为政策干预提供信息对于确保医疗保健系统的网络安全至关重要.
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