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<meta name="description" content="论文来源:USENIX SECURITY 2018下载:原文pdf中文slides 论文解读1. 概要: 物联网(IoT)设备的快速增长的格局为其管理和安全性带来了重大的技术挑战,因为这些物联网设备来自不同的设备类型,供应商和产品模型。 物联网设备的发现是表征,监控和保护这些设备的先决条件。然而,手动设备注释阻碍了大规模发现,并且基于机器学习的设备分类需要具有标签的大型训练数据。因此,大规模">
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<meta name="description" content="论文来源:USENIX SECURITY 2018下载:原文pdf中文slides 论文解读1. 概要: 物联网(IoT)设备的快速增长的格局为其管理和安全性带来了重大的技术挑战,因为这些物联网设备来自不同的设备类型,供应商和产品模型。 物联网设备的发现是表征,监控和保护这些设备的先决条件。然而,手动设备注释阻碍了大规模发现,并且基于机器学习的设备分类需要具有标签的大型训练数据。因此,大规模">
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<meta property="og:description" content="论文来源:USENIX SECURITY 2018下载:原文pdf中文slides 论文解读1. 概要: 物联网(IoT)设备的快速增长的格局为其管理和安全性带来了重大的技术挑战,因为这些物联网设备来自不同的设备类型,供应商和产品模型。 物联网设备的发现是表征,监控和保护这些设备的先决条件。然而,手动设备注释阻碍了大规模发现,并且基于机器学习的设备分类需要具有标签的大型训练数据。因此,大规模">
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<meta property="og:description" content="论文来源:USENIX SECURITY 2018下载:原文pdf中文slides 论文解读1. 概要: 物联网(IoT)设备的快速增长的格局为其管理和安全性带来了重大的技术挑战,因为这些物联网设备来自不同的设备类型,供应商和产品模型。 物联网设备的发现是表征,监控和保护这些设备的先决条件。然而,手动设备注释阻碍了大规模发现,并且基于机器学习的设备分类需要具有标签的大型训练数据。因此,大规模">
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<meta name="twitter:description" content="论文来源:USENIX SECURITY 2018下载:原文pdf中文slides 论文解读1. 概要: 物联网(IoT)设备的快速增长的格局为其管理和安全性带来了重大的技术挑战,因为这些物联网设备来自不同的设备类型,供应商和产品模型。 物联网设备的发现是表征,监控和保护这些设备的先决条件。然而,手动设备注释阻碍了大规模发现,并且基于机器学习的设备分类需要具有标签的大型训练数据。因此,大规模">
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<meta name="twitter:description" content="论文来源:USENIX SECURITY 2018下载:原文pdf中文slides 论文解读1. 概要: 物联网(IoT)设备的快速增长的格局为其管理和安全性带来了重大的技术挑战,因为这些物联网设备来自不同的设备类型,供应商和产品模型。 物联网设备的发现是表征,监控和保护这些设备的先决条件。然而,手动设备注释阻碍了大规模发现,并且基于机器学习的设备分类需要具有标签的大型训练数据。因此,大规模">
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<title>基于规则引擎发现IOT设备 | 混元霹雳手</title>
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<title>Acquisitional Rule-based Engine for Discovering Internet-of-Things Devices | 混元霹雳手</title>
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<h1 class="post-title" itemprop="name headline">基于规则引擎发现IOT设备</h1>
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<h1 class="post-title" itemprop="name headline">Acquisitional Rule-based Engine for Discovering Internet-of-Things Devices</h1>
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