Using Human-Centred Appraoch and ML Techniques to Automate/ Visualise Anomaly and Vulnerability Detection in Critical Communication Systems Context

使用以人为本的方法和机器学习技术来自动化/可视化关键通信系统环境中的异常和漏洞检测

• 批准号: 2758934
• 金额: --
• 依托单位: Swansea University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2758934
• 关键词: Using; Human; Centred; Appraoch; ML

The impact on ISUS Consulting clients will be to streamline their processes for designing testbeds of experimental wireless networks. The next generation emulator will enhance the interactivity with the simulated wireless network with the user interfaces and visualisations automatically adapting to various contexts (such as user role (e.g., novice vs expert), resource constraints (e.g., bandwidth strength)) and visualising automatically detected system anomalies and vulnerabilities. The implementation of this tool will have further downstream impact by enabling faster turnaround times when emulating/simulating wireless network scenarios.

对ISUS咨询公司客户的影响将是简化他们设计实验性无线网络测试平台的流程。下一代模拟器将增强与模拟无线网络的交互性，通过用户界面和可视化自动适应各种上下文（例如用户角色（例如新手与专家），资源约束（例如带宽强度））和可视化自动检测系统异常和漏洞。该工具的实现将在模拟/模拟无线网络场景时实现更快的周转时间，从而对下游产生进一步的影响。