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< h1 class = "post-title" itemprop = "name headline" > 基于采集规则引擎的物联网设备发现方法< / h1 >
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< p > < strong > < em > 论文来源：< / em > < / strong > USENIX SECURITY 2018： < br > < strong > < em > 下载：< / em > < / strong > < br > < a href = "https://www.usenix.org/conference/usenixsecurity18/presentation/feng" target = "_blank" rel = "noopener" > 原文pdf< / a > < br > < a href = "https://res.cloudinary.com/dozyfkbg3/raw/upload/v1553314438/ARE/Rule-based_engine.pptx" target = "_blank" rel = "noopener" > 中文slides< / a > < / p >
< h2 id = "论文解读" > < a href = "#论文解读" class = "headerlink" title = "论文解读" > < / a > 论文解读< / h2 > < h3 id = "概要：" > < a href = "#概要：" class = "headerlink" title = "概要：" > < / a > 概要：< / h3 > < ul >
< li > 物联网（ ） ， ， < / li >
< li > 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，大规模的自动设备发现和注释仍然是物联网中的一个悬而未决的问题。< / li >
< li > 这篇文章提出了一种基于采集规则的引擎（ ） ， ， < / li >
< li > 为了收集交易集， （ ， ） < / li >
< / ul >
< h3 id = "背景与动机：" > < a href = "#背景与动机：" class = "headerlink" title = "背景与动机：" > < / a > 背景与动机：< / h3 > < ul >
< li > 物联网蓬勃发展， ， ， ， ， ， < / li >
< li > 但是由于设备脆弱、缺乏管理和配置不当， ， ， ， ， < / li >
< li > 设备注释的内容通常为“设备类型(e.g.,routers) + 供应商(e.g.,CISCO) + 产品型号(e.g.,TV-IP302P)”，传统生成设备注释的方法有基于指纹的，也有使用标志获取的，前者对数据集和大量设备模型的要求很高，而后者需要专业知识的人工方式，因此不可能用于大规模注释而且很难去维护更新。< / li >
< / ul >
< p > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1553313806/ARE/1.png" alt > < / p >
< p > 所以， ， ， （ ） ， ， ， ， ， < / p >
< h3 id = "核心工作—Rule-Miner： > < a href = "#核心工作—Rule-Miner： class = "headerlink" title = "核心工作—Rule Miner： > < / a > 核心工作—Rule Miner： < / h3 > < p > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1553313904/ARE/2.png" alt > < / p >
< p > Rule Miner由三个部分构成， ， ： ， ， ； ， ， ， < / p >
< h3 id = "完整架构和应用" > < a href = "#完整架构和应用" class = "headerlink" title = "完整架构和应用" > < / a > 完整架构和应用< / h3 > < p > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1553313904/ARE/4.png" alt > < / p >
< p > 完整的ARE除了核心Rule Miner之外， ， ， < br > 作者主要将ARE应用于三个方面， ， ， < br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1553313946/ARE/6.png" alt > < br > 之后对ARE的效果与Nmap进行比较和评估， ， < br > < img src = "https://res.cloudinary.com/dozyfkbg3/image/upload/v1553313805/ARE/5.png" alt > < / p >
< h3 id = "工作总结：" > < a href = "#工作总结：" class = "headerlink" title = "工作总结：" > < / a > 工作总结：< / h3 > < ul >
< li > 提出ARE的框架： ， < / li >
< li > 实现了ARE的原型并评估了它的效果： ， < / li >
< li > 应用于三个场景中， ： ； < / li >
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});
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$(function() {
var Counter = AV.Object.extend("Counter");
if ($('.leancloud_visitors').length == 1) {
addCount(Counter);
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