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Logistics Exceptions Monitoring for Anti-counterfeiting in RFID-Enabled Supply Chains

机译:Logistics例外监控用于RFID的供应链中的防伪

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In recent years, the radio frequency identification (RFID) technology has been used as a promising tool for anti-counterfeiting in RFID-enabled supply chains due to its track-and-trace abilities of contactless object identification with the unique electronic product code (EPC). While this system does improve its performance in many ways, uncertainties of daily operations might bring about one or more logistics exceptions, which would further trigger other dependent exceptions. These exceptions could be well organized and exploited by adversaries to fool the system for counterfeiting while related reports are unfortunately very few. In this paper, we presented our results focusing on the inter-dependencies between those logistics exceptions and the detecting intelligence in a resource-centric view. A cause-effect relational diagram is first developed to explicitly express the relations among those logistics exceptions by incorporating the taxonomy of exceptions and resource-based theory, and then an improved intelligent exception monitoring system is designed to achieve the goal of autonomous, flexible, collaborative and reliable logistics services. Finally, a case study of two typical logistics exceptions indicates that our proposed cause-effect diagram outperforms the extant approaches in the understanding of group logistics exceptions, which enables the designed monitoring system to perform well for anti-counterfeiting.
机译:近年来,射频识别(RFID)技术已被用作可承诺的工具,用于防伪抵消支持的RFID供应链,这是由于其具有独特电子产品代码(EPC)的非接触式对象识别的跟踪和跟踪能力)。虽然该系统以多种方式提高其性能,但日常运营的不确定性可能会带来一个或多个物流异常,这将进一步触发其他受抚养例外的例外。这些例外可能是由对手来欺骗的对手来欺骗制度,而不幸的是,不幸的是,很少有相关的报告。在本文中,我们介绍了我们的结果,专注于这些物流异常与资源为中心的检测智能之间的依赖关系。首先开发出致原因关系图以通过纳入例外和基于资源的理论的分类,明确表达这些物流例外的关系,然后旨在实现自主,灵活,协作的目标。可靠的物流服务。最后,对两个典型物流例外的案例研究表明,我们所提出的原因效果图优越,优于对集团物流例外的理解中的现存方法,这使得设计的监控系统能够对抗伪造。

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