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作 者:诸邵忆 ZHU Shao-yi(Zhejiang Police Vocational Academy,Hangzhou,Zhejiang 310018,China)
出 处:《杨凌职业技术学院学报》2025年第1期13-18,40,共7页Journal of Yangling Vocational & Technical College
基 金:2024年度浙江省教育厅一般科研项目“高安全场景下基于RFID的目标感知及载体管控技术研究”(Y202454357)。
摘 要:针对长期以来单位内部物理载体管控缺位导致的敏感信息泄露问题,提出基于RFID技术的载体全生命周期管控体系,在登记、借阅、盘点、回收等流程的基础上,利用部署在单位管控场所边界处的RFID监控系统对重要载体进行被动式监管,设计基于自组织神经网络的智能出入检测模型用以精确区分载体正常室内使用及载体被携带经过管控边界这两种情况,提出基于滑动窗口的实时监测方案,并对窗口大小及重叠率进行了大量实验。结果表明,智能出入检测系统能够在确保实时性能的同时保证高检出率和低误报率。In response to the problem of sensitive information leakage caused by the lack of internal physical carrier control in units for a long time,a carrier lifecycle control system based on RFID technology is proposed.Based on the processes of registration,borrowing,inventory,and recycling,an RFID monitoring system deployed at the boundary of the unit control site is used to comprehensively supervise important carriers.An intelligent access detection model based on self-organizing neural networks is designed to distinguish between normal indoor use of carriers and carriers carried through the control boundary.A real-time monitoring scheme based on sliding windows is proposed,and a large number of experiments are conducted on window size and overlap rate.The results indicate that the intelligent access detection system can ensure high detection rate and low false alarm rate while ensuring real-time performance.
分 类 号:TP391.4[自动化与计算机技术—计算机应用技术]
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