启用物联网智能城市系统中的网络安全基准和风险缓解:Hradec Kralove地区的案例研究
Vladimir Sobeslav1, Josef Horalek1
1Faculty of Informatics and Management, University of Hradec Kralove, 500 03 Hradec Kralove, Czech Republic.
Sensors (Basel, Switzerland)
|August 28, 2025
概括
本研究提出了智能城市开放数据的网络安全风险模型,使用自动化分析来识别关键数据流和影响. 它优先考虑城市数字基础设施的数据保护措施.
科学领域:
- 网络安全
- 智慧城市技术
- 数据管理
背景情况:
- 智能城市倡议越来越依赖于开放数据,引入独特的网络安全挑战.
- 有效的风险建模对于保护敏感信息和确保服务连续性至关重要.
研究的目的:
- 开发和验证智能城市环境中开放数据的网络安全风险建模框架.
- 通过自动化分析和业务影响分析 (BIA) 建立网络安全基准.
主要方法:
- 使用扩展的业务流程模型和符号 (BPMN) 进行流程映射和自动化分析.
- 综合业务影响分析 (BIA) 量化中断影响 (RTO,MTPD,MTDL).
- 开发了一个自动选择风险缓解策略的框架.
主要成果:
- 确定了关键数据流并量化了它们对中断的耐受性.
- 在开放数据中的可视化-发布过程显示出对中断的高度耐受性,但需要强大的保密性和完整性.
- 定义的最大可承受的数据丢失 (MTDL) 为24小时,导致具体的安全措施建议 (加密,访问控制,备份).
结论:
- 将流程映射与安全要求相结合,有效地优先考虑智能城市的数据保护.
- 拟议的方法提高了数据的可用性和完整性,有助于城市数字基础设施的弹性.
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