Intruder alert! detecting and classifying events in noisy time series

入侵者警报！

• 批准号: LP160101885
• 负责人: Prof Robin Hyndman
• 金额: $ 14.27万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2017
• 资助国家: 澳大利亚
• 起止时间: 2017-09-06 至 2019-09-06
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP160101885
• 关键词: Intruder; alert; detecting; classifying; events

This project aims to address the mathematical challenges in automated early detection and classification of intrusion events in noisy time series generated from perimeter security systems. The project expects to develop robust methods to detect intrusion events under different operating environments while ignoring nuisance events. The project will boost the global competitiveness of the Australian security industry, and enable improved event detection and classification in noisy time series to the benefit of many critical application areas beyond national security.

该项目旨在解决自动早期检测和分类的噪声时间序列从周边安全系统中产生的入侵事件的数学挑战。该项目期望开发鲁棒的方法来检测不同操作环境下的入侵事件，同时忽略滋扰事件。该项目将提高澳大利亚安全行业的全球竞争力，并在嘈杂的时间序列中改进事件检测和分类，从而使国家安全以外的许多关键应用领域受益。