1420 lines
51 KiB
HTML
1420 lines
51 KiB
HTML
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<!DOCTYPE html>
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<html class="theme-next gemini use-motion" lang="zh-Hans">
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<head><meta name="generator" content="Hexo 3.8.0">
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<meta charset="UTF-8">
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<meta http-equiv="X-UA-Compatible" content="IE=edge">
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<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1">
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<meta name="theme-color" content="#222">
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<meta http-equiv="Cache-Control" content="no-transform">
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<meta http-equiv="Cache-Control" content="no-siteapp">
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<link href="/lib/fancybox/source/jquery.fancybox.css?v=2.1.5" rel="stylesheet" type="text/css">
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<link href="/lib/font-awesome/css/font-awesome.min.css?v=4.6.2" rel="stylesheet" type="text/css">
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<link href="/css/main.css?v=5.1.4" rel="stylesheet" type="text/css">
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<link rel="apple-touch-icon" sizes="180x180" href="/images/hackerrank.png?v=5.1.4">
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<link rel="icon" type="image/png" sizes="32x32" href="/images/hackerrank.png?v=5.1.4">
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<link rel="icon" type="image/png" sizes="16x16" href="/images/hackerrank.png?v=5.1.4">
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<link rel="mask-icon" href="/images/logo.svg?v=5.1.4" color="#222">
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<meta name="keywords" content="硬件攻击,传感器,语音助手,">
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<meta name="description" content="海豚音攻击-复现文章中提到两种方案，一是具有信号发生器的强大变送器，二是带有智能手机的便携式变送器；前一种方案成本过于高，本文不做分析，后一种方案的实现成本在我们可接收的范围。但原文中对后一方案的实现没有太多介绍，于是我通过邮件咨询了作者-闫琛博士，闫博士非常友好，我是在晚上十点发送的第一封邮件，差不多在十分钟内通过几封邮件的交流，解决了我的问题，很快确定了我的具体实现路径，非常感谢大佬！ Q:">
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<meta name="keywords" content="硬件攻击,传感器,语音助手">
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<meta property="og:type" content="article">
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<meta property="og:title" content="Dolphin Attack 论文复现">
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<meta property="og:url" content="https://cool-y.github.io/2021/01/08/dolphin-attack-practice/index.html">
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<meta property="og:site_name" content="混元霹雳手">
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<meta property="og:description" content="海豚音攻击-复现文章中提到两种方案，一是具有信号发生器的强大变送器，二是带有智能手机的便携式变送器；前一种方案成本过于高，本文不做分析，后一种方案的实现成本在我们可接收的范围。但原文中对后一方案的实现没有太多介绍，于是我通过邮件咨询了作者-闫琛博士，闫博士非常友好，我是在晚上十点发送的第一封邮件，差不多在十分钟内通过几封邮件的交流，解决了我的问题，很快确定了我的具体实现路径，非常感谢大佬！ Q:">
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<meta property="og:locale" content="zh-Hans">
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<meta property="og:image" content="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082052/Dolphin%20Attack/08_YW7UW_PS_TOE_LZZY.png">
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<meta property="og:image" content="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082052/Dolphin%20Attack/WGD_U453KYP3M3_2639_5I.png">
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<meta property="og:image" content="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082051/Dolphin%20Attack/K5447O57_S___A_O_Q3V.png">
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<meta property="og:image" content="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082052/Dolphin%20Attack/OPSXK_21_7R24_I_NIWM0_8.png">
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<meta property="og:image" content="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082051/Dolphin%20Attack/G8_K4_ZG__PE2CQ_5_UYY.png">
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<meta property="og:image" content="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082508/Dolphin%20Attack/Snipaste_2021-01-08_13-06-55.png">
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<meta property="og:updated_time" content="2021-01-08T05:21:51.940Z">
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<meta name="twitter:card" content="summary">
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<meta name="twitter:title" content="Dolphin Attack 论文复现">
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<meta name="twitter:description" content="海豚音攻击-复现文章中提到两种方案，一是具有信号发生器的强大变送器，二是带有智能手机的便携式变送器；前一种方案成本过于高，本文不做分析，后一种方案的实现成本在我们可接收的范围。但原文中对后一方案的实现没有太多介绍，于是我通过邮件咨询了作者-闫琛博士，闫博士非常友好，我是在晚上十点发送的第一封邮件，差不多在十分钟内通过几封邮件的交流，解决了我的问题，很快确定了我的具体实现路径，非常感谢大佬！ Q:">
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<meta name="twitter:image" content="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082052/Dolphin%20Attack/08_YW7UW_PS_TOE_LZZY.png">
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<script type="text/javascript" id="hexo.configurations">
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var NexT = window.NexT || {};
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var CONFIG = {
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root: '/',
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scheme: 'Gemini',
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version: '5.1.4',
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sidebar: {"position":"left","display":"post","offset":12,"b2t":false,"scrollpercent":false,"onmobile":false},
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fancybox: true,
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tabs: true,
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motion: {"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}},
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duoshuo: {
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userId: '0',
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author: '博主'
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},
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algolia: {
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applicationID: '',
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apiKey: '',
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indexName: '',
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hits: {"per_page":10},
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labels: {"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}
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}
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};
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</script>
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<link rel="canonical" href="https://cool-y.github.io/2021/01/08/dolphin-attack-practice/">
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<title>Dolphin Attack 论文复现 | 混元霹雳手</title>
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</head>
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<body itemscope itemtype="http://schema.org/WebPage" lang="zh-Hans">
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<div class="container sidebar-position-left page-post-detail">
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<div class="headband"></div>
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<header id="header" class="header" itemscope itemtype="http://schema.org/WPHeader">
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<div class="header-inner"><div class="site-brand-wrapper">
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<div class="site-meta ">
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<div class="custom-logo-site-title">
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<a href="/" class="brand" rel="start">
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<span class="logo-line-before"><i></i></span>
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<span class="site-title">混元霹雳手</span>
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<span class="logo-line-after"><i></i></span>
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</a>
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</div>
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<p class="site-subtitle"></p>
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</div>
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<div class="site-nav-toggle">
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<button>
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<span class="btn-bar"></span>
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<span class="btn-bar"></span>
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<span class="btn-bar"></span>
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</button>
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</div>
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</div>
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<nav class="site-nav">
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<ul id="menu" class="menu">
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<li class="menu-item menu-item-home">
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<a href="/" rel="section">
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<i class="menu-item-icon fa fa-fw fa-home"></i> <br>
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首页
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</a>
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</li>
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<li class="menu-item menu-item-about">
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<a href="/about/" rel="section">
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<i class="menu-item-icon fa fa-fw fa-user"></i> <br>
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关于
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</a>
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</li>
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<li class="menu-item menu-item-tags">
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<a href="/tags/" rel="section">
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<i class="menu-item-icon fa fa-fw fa-tags"></i> <br>
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标签
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</a>
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</li>
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<li class="menu-item menu-item-categories">
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<a href="/categories/" rel="section">
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<i class="menu-item-icon fa fa-fw fa-th"></i> <br>
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分类
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</a>
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</li>
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<li class="menu-item menu-item-archives">
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<a href="/archives/" rel="section">
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<i class="menu-item-icon fa fa-fw fa-archive"></i> <br>
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归档
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</a>
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</li>
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<li class="menu-item menu-item-bookmarks">
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<a href="/bookmarks/" rel="section">
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<i class="menu-item-icon fa fa-fw fa-map"></i> <br>
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书签
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</a>
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</li>
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<li class="menu-item menu-item-hack之外">
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<a href="/hack之外/" rel="section">
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<i class="menu-item-icon fa fa-fw fa-heartbeat"></i> <br>
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HACK之外
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</a>
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</li>
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<li class="menu-item menu-item-search">
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<a href="javascript:;" class="popup-trigger">
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<i class="menu-item-icon fa fa-search fa-fw"></i> <br>
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搜索
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</a>
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</li>
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</ul>
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<div class="site-search">
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|||
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<div class="popup search-popup local-search-popup">
|
|||
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<div class="local-search-header clearfix">
|
|||
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<span class="search-icon">
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|||
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<i class="fa fa-search"></i>
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|||
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</span>
|
|||
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<span class="popup-btn-close">
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|||
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<i class="fa fa-times-circle"></i>
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|||
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</span>
|
|||
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<div class="local-search-input-wrapper">
|
|||
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<input autocomplete="off" placeholder="搜索..." spellcheck="false" type="text" id="local-search-input">
|
|||
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</div>
|
|||
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</div>
|
|||
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<div id="local-search-result"></div>
|
|||
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</div>
|
|||
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</div>
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</nav>
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|||
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</div>
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</header>
|
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<main id="main" class="main">
|
|||
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<div class="main-inner">
|
|||
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<div class="content-wrap">
|
|||
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<div id="content" class="content">
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|||
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|
|||
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|||
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<div id="posts" class="posts-expand">
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<article class="post post-type-normal" itemscope itemtype="http://schema.org/Article">
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|||
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<div class="post-block">
|
|||
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<link itemprop="mainEntityOfPage" href="https://cool-y.github.io/2021/01/08/dolphin-attack-practice/">
|
|||
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|
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<span hidden itemprop="author" itemscope itemtype="http://schema.org/Person">
|
|||
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<meta itemprop="name" content="Cool-Y">
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<meta itemprop="description" content>
|
|||
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<meta itemprop="image" content="/images/avatar.png">
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|||
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</span>
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|||
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|
|||
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<span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization">
|
|||
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<meta itemprop="name" content="混元霹雳手">
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|||
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</span>
|
|||
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|
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|
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<header class="post-header">
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|||
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|
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<h1 class="post-title" itemprop="name headline">Dolphin Attack 论文复现</h1>
|
|||
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|
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|
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<div class="post-meta">
|
|||
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<span class="post-time">
|
|||
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|
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<h1 id="海豚音攻击-复现"><a href="#海豚音攻击-复现" class="headerlink" title="海豚音攻击-复现"></a>海豚音攻击-复现</h1><p>文章中提到两种方案，一是具有信号发生器的强大变送器，二是带有智能手机的便携式变送器；前一种方案成本过于高，本文不做分析，后一种方案的实现成本在我们可接收的范围。<br>但原文中对后一方案的实现没有太多介绍，于是我通过邮件咨询了作者-闫琛博士，闫博士非常友好，我是在晚上十点发送的第一封邮件，差不多在十分钟内通过几封邮件的交流，解决了我的问题，很快确定了我的具体实现路径，非常感谢大佬！</p>
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<ul>
|
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<li>Q: 使用便携式设备攻击的时候，三星Galaxy S6 Edge发送的高频声音信号是怎么生成的呢？是预先使用专业设备调制好的信号保存为mp3吗？</li>
|
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<li>A: 通过软件调制，生成.wav的超声波音频文件，再通过三星手机播放的。</li>
|
|||
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<li>Q: 用的是什么软件进行调制?</li>
|
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<li>A: 用过matlab和python，都是可以的</li>
|
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<h2 id="0x01-语音命令生成"><a href="#0x01-语音命令生成" class="headerlink" title="0x01 语音命令生成"></a>0x01 语音命令生成</h2><p><a href="https://ttstool.com/" target="_blank" rel="noopener">https://ttstool.com/</a><br>微软的TTS接口生成的是mp3格式音频，一般来说我们使用python处理音频都是针对wav格式。<br><a href="https://www.aconvert.com/cn/audio/mp3-to-wav/" target="_blank" rel="noopener">https://www.aconvert.com/cn/audio/mp3-to-wav/</a><br>我们可以通过这个网站对格式做转换。<br><a href="https://coolyim.quip.com/-/blob/OVVAAAmjZcr/Eq9qXdQ7_eD5KQaR33wCCw?name=xiaoyi.wav" target="_blank" rel="noopener">xiaoyi.wav</a><br>这个网站的采样率最高只能达到96000hz<br><a href="https://coolyim.quip.com/-/blob/OVVAAAmjZcr/aZfltfEV_ZxV1LCGznB1OA?name=6wxmu-crusr.wav" target="_blank" rel="noopener">6wxmu-crusr.wav</a></p>
|
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<h2 id="0x02-语音命令调制"><a href="#0x02-语音命令调制" class="headerlink" title="0x02 语音命令调制"></a>0x02 语音命令调制</h2><p>生成语音命令的基带信号后，我们需要在超声载波上对其进行调制，以使它们听不到。 为了利用麦克风的非线性，DolphinAttack必须利用幅度调制（AM）。</p>
|
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<h3 id="AM调制原理"><a href="#AM调制原理" class="headerlink" title="AM调制原理"></a>AM调制原理</h3><p>使载波的振幅按照所需传送信号的变化规律而变化，但频率保持不变的调制方法。调幅在有线电或无线电通信和广播中应用甚广。调幅是高频载波的振幅随信号改变的调制（AM）。其中，载波信号的振幅随着调制信号的某种特征的变换而变化。例如，0或1分别对应于无载波或有载波输出，电视的图像信号使用调幅。调频的抗干扰能力强，失真小，但服务半径小。<br>假设载波uc(t)和调制信号的频率分别为ωc和Ω，在已调波中包含三个频率成分：ωc、ωc+Ω和ωc-Ω。ωc+Ω称为上边频，ωc-Ω称为下边频。</p>
|
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<p><a href="https://epxx.co/artigos/ammodulation.html" target="_blank" rel="noopener">https://epxx.co/artigos/ammodulation.html</a><br><a href="http://www.chenjianqu.com/show-44.html" target="_blank" rel="noopener">http://www.chenjianqu.com/show-44.html</a><br><a href="https://zhuanlan.zhihu.com/p/54561504" target="_blank" rel="noopener">https://zhuanlan.zhihu.com/p/54561504</a><br><a href="http://www.mwhitelab.com/archives/208" target="_blank" rel="noopener">http://www.mwhitelab.com/archives/208</a></p>
|
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<h3 id="使用python调制"><a href="#使用python调制" class="headerlink" title="使用python调制"></a>使用python调制</h3><p>现在我们已经有了基带信号，使用<a href="https://www.fosshub.com/Audacity.html" target="_blank" rel="noopener">Audacity</a>对其进行频谱分析，此语音的带宽或频谱（左图为采样频率48khz音频，右图为96khz） ：<br><img src="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082052/Dolphin%20Attack/08_YW7UW_PS_TOE_LZZY.png" alt><br><img src="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082052/Dolphin%20Attack/WGD_U453KYP3M3_2639_5I.png" alt></p>
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<p>我们可以看到带宽为8000-9000hz左右，这是女声，因此频带范围较宽。这可能导致可听范围内的频率泄露，但这里我们先不去讨论，之后再使用带宽较小的语音以创建基带语音信号。<br>wave包最多能读取的wav音频采样率为<a href="https://github.com/jiaaro/pydub/issues/134" target="_blank" rel="noopener">48khz</a>，当超过这个值时，wave就不再支持（wave.Error: unknown format: 65534）。但我们的载波频率为30khz左右，这就要求音频文件的采样率高于60khz才能保证不失真。所幸<a href="https://kite.com/python/docs/scipy.io.wavfile" target="_blank" rel="noopener"><code>scipy.io.wavfile</code></a>支持高于48khz的wav文件读取。<br>使用以下Python程序来生成调制的AM和AM-SC音频，AM是广播无线电调制的“正常”声音，它加上了载波；AM-SC则只是载波与原始信号的乘积。</p>
|
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<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># coding=utf-8</span></span><br><span class="line"><span class="keyword">import</span> numpy <span class="keyword">as</span> np</span><br><span class="line"><span class="keyword">import</span> matplotlib.pyplot <span class="keyword">as</span> plt</span><br><span class="line"><span class="keyword">import</span> os</span><br><span class="line"><span class="keyword">import</span> wave</span><br><span class="line"><span class="keyword">import</span> struct</span><br><span class="line"><span class="keyword">import</span> math</span><br><span class="line"><span class="keyword">from</span> pydub <span class="keyword">import</span> AudioSegment</span><br><span class="line"><span class="keyword">import</span> scipy.io.wavfile</span><br><span class="line"></span><br><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">main</span><span class="params">()</span>:</span></span><br><span class="line"> test = scipy.io.wavfile.read(<span class="string">"xiaoyi.wav"</span>)</span><br><span class="line"> nframes = len(test[<span class="number">1</span>])</span><br><span class="line"> waveData = np.fromstring(test[<span class="number">1</span>],dtype=np.short)<span class="comment">#将原始字符数据转换为整数</span></span><br><span class="line"> <span class="comment">#音频数据归一化</span></span><br><span class="line"> maxW = max(abs(waveData))</span><br><span class="line"> waveData = waveData * <span class="number">1.0</span>/maxW</span><br><span class="line"> <span class="comment">#将音频信号规整乘每行一路通道信号的格式，即该矩阵一行为一个通道的采样点，共nchannels行</span></span><br><span class="line"> Tdata = np.reshape(waveData,[nframes,<span class="number">1</span>]).T <span class="comment"># .T 表示转置</span></span><br><span class="line"> am = wave.open(<span class="string">"am.wav"</span>, <span class="string">"w"</span>)</span><br><span class="line"> amsc = wave.open(<span class="string">"amsc.wav"</span>, <span class="string">"w"</span>)</span><br><span class="line"> carrier = wave.open(<span class="string">"carrier3000.wav"</span>, <span class="string">"w"</span>)</span><br><span class="line"> <span class="keyword">for</span> f <span class="keyword">in</span> [am,amsc,carrier]:</span><br><span class="line"> f.setnchannels(<span class="number">1</span>)</span><br><span class="line"> f.setsampwidth(<span class="number">2</span>)</span><br><span class="line"> f.setframerate(<span class="number">96000</span>)</span><br><span class="line"> <span class="keyword">for</span> n <span class="keyword">in</span> range(<span class="number">0</span>, nframes):</s
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<p>分别对am.wav、amsc.wav、carrier3000.wav做频谱分析<br>carrier3000.wav的频谱的为集中在载波频率30khz上的一个脉冲<a href="https://coolyim.quip.com/-/blob/OVVAAAmjZcr/9RE4Z0lCs1WACO75zLTAhA?name=carrier3000.wav" target="_blank" rel="noopener">carrier3000.wav</a><br><img src="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082051/Dolphin%20Attack/K5447O57_S___A_O_Q3V.png" alt><br>amsc.wav的带宽约为18khz，是原来的两倍，关于f=30khz镜面对称。AM调制会创建原始信号的两个“副本”，一个在21-30kHz频段，另一个在30-39kHz。<br><img src="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082052/Dolphin%20Attack/OPSXK_21_7R24_I_NIWM0_8.png" alt></p>
|
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<p>am.wav，在这种调制中，我们可以听到载波，而在AM-SC中则听不到。频谱类似于AM-SC，但在载波频率上还有一个尖锐的“尖峰”：<br><img src="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082051/Dolphin%20Attack/G8_K4_ZG__PE2CQ_5_UYY.png" alt></p>
|
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<h2 id="0x03-语音命令发送器"><a href="#0x03-语音命令发送器" class="headerlink" title="0x03 语音命令发送器"></a>0x03 语音命令发送器</h2><p>下图是由智能手机驱动的便携式发射器。便携式发射器利用智能手机来发射调制信号。许多设备的最佳载波频率都大于24 kHz， 大多数智能手机无法完成任务。大多数智能手机最多支持48 kHz采样率，所以只能发送载波频率最高为24 kHz的调制窄带信号。需要支持高达192 kHz的采样率的手机，而且扬声器会衰减频率大于20 kHz的信号。为了减轻这个问题，我使用窄带超声换能器作为扬声器，并在超声换能器之前添加了一个放大器，这样有效的攻击范围得以扩展。</p>
|
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<p><img src="https://res.cloudinary.com/dozyfkbg3/image/upload/v1610082508/Dolphin%20Attack/Snipaste_2021-01-08_13-06-55.png" alt></p>
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<i class="fa fa-chevron-left"></i> Dolphin Attack 论文翻译
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<iframe frameborder="no" border="0" marginwidth="0" marginheight="0" width="330" height="450" src="//music.163.com/outchain/player?type=4&id=334277093&auto=1&height=430"></iframe>
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|
|||
|
|
<script type="text/javascript">
|
|||
|
|
// Popup Window;
|
|||
|
|
var isfetched = false;
|
|||
|
|
var isXml = true;
|
|||
|
|
// Search DB path;
|
|||
|
|
var search_path = "search.xml";
|
|||
|
|
if (search_path.length === 0) {
|
|||
|
|
search_path = "search.xml";
|
|||
|
|
} else if (/json$/i.test(search_path)) {
|
|||
|
|
isXml = false;
|
|||
|
|
}
|
|||
|
|
var path = "/" + search_path;
|
|||
|
|
// monitor main search box;
|
|||
|
|
|
|||
|
|
var onPopupClose = function (e) {
|
|||
|
|
$('.popup').hide();
|
|||
|
|
$('#local-search-input').val('');
|
|||
|
|
$('.search-result-list').remove();
|
|||
|
|
$('#no-result').remove();
|
|||
|
|
$(".local-search-pop-overlay").remove();
|
|||
|
|
$('body').css('overflow', '');
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
function proceedsearch() {
|
|||
|
|
$("body")
|
|||
|
|
.append('<div class="search-popup-overlay local-search-pop-overlay"></div>')
|
|||
|
|
.css('overflow', 'hidden');
|
|||
|
|
$('.search-popup-overlay').click(onPopupClose);
|
|||
|
|
$('.popup').toggle();
|
|||
|
|
var $localSearchInput = $('#local-search-input');
|
|||
|
|
$localSearchInput.attr("autocapitalize", "none");
|
|||
|
|
$localSearchInput.attr("autocorrect", "off");
|
|||
|
|
$localSearchInput.focus();
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
// search function;
|
|||
|
|
var searchFunc = function(path, search_id, content_id) {
|
|||
|
|
'use strict';
|
|||
|
|
|
|||
|
|
// start loading animation
|
|||
|
|
$("body")
|
|||
|
|
.append('<div class="search-popup-overlay local-search-pop-overlay">' +
|
|||
|
|
'<div id="search-loading-icon">' +
|
|||
|
|
'<i class="fa fa-spinner fa-pulse fa-5x fa-fw"></i>' +
|
|||
|
|
'</div>' +
|
|||
|
|
'</div>')
|
|||
|
|
.css('overflow', 'hidden');
|
|||
|
|
$("#search-loading-icon").css('margin', '20% auto 0 auto').css('text-align', 'center');
|
|||
|
|
|
|||
|
|
$.ajax({
|
|||
|
|
url: path,
|
|||
|
|
dataType: isXml ? "xml" : "json",
|
|||
|
|
async: true,
|
|||
|
|
success: function(res) {
|
|||
|
|
// get the contents from search data
|
|||
|
|
isfetched = true;
|
|||
|
|
$('.popup').detach().appendTo('.header-inner');
|
|||
|
|
var datas = isXml ? $("entry", res).map(function() {
|
|||
|
|
return {
|
|||
|
|
title: $("title", this).text(),
|
|||
|
|
content: $("content",this).text(),
|
|||
|
|
url: $("url" , this).text()
|
|||
|
|
};
|
|||
|
|
}).get() : res;
|
|||
|
|
var input = document.getElementById(search_id);
|
|||
|
|
var resultContent = document.getElementById(content_id);
|
|||
|
|
var inputEventFunction = function() {
|
|||
|
|
var searchText = input.value.trim().toLowerCase();
|
|||
|
|
var keywords = searchText.split(/[\s\-]+/);
|
|||
|
|
if (keywords.length > 1) {
|
|||
|
|
keywords.push(searchText);
|
|||
|
|
}
|
|||
|
|
var resultItems = [];
|
|||
|
|
if (searchText.length > 0) {
|
|||
|
|
// perform local searching
|
|||
|
|
datas.forEach(function(data) {
|
|||
|
|
var isMatch = false;
|
|||
|
|
var hitCount = 0;
|
|||
|
|
var searchTextCount = 0;
|
|||
|
|
var title = data.title.trim();
|
|||
|
|
var titleInLowerCase = title.toLowerCase();
|
|||
|
|
var content = data.content.trim().replace(/<[^>]+>/g,"");
|
|||
|
|
var contentInLowerCase = content.toLowerCase();
|
|||
|
|
var articleUrl = decodeURIComponent(data.url);
|
|||
|
|
var indexOfTitle = [];
|
|||
|
|
var indexOfContent = [];
|
|||
|
|
// only match articles with not empty titles
|
|||
|
|
if(title != '') {
|
|||
|
|
keywords.forEach(function(keyword) {
|
|||
|
|
function getIndexByWord(word, text, caseSensitive) {
|
|||
|
|
var wordLen = word.length;
|
|||
|
|
if (wordLen === 0) {
|
|||
|
|
return [];
|
|||
|
|
}
|
|||
|
|
var startPosition = 0, position = [], index = [];
|
|||
|
|
if (!caseSensitive) {
|
|||
|
|
text = text.toLowerCase();
|
|||
|
|
word = word.toLowerCase();
|
|||
|
|
}
|
|||
|
|
while ((position = text.indexOf(word, startPosition)) > -1) {
|
|||
|
|
index.push({position: position, word: word});
|
|||
|
|
startPosition = position + wordLen;
|
|||
|
|
}
|
|||
|
|
return index;
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
indexOfTitle = indexOfTitle.concat(getIndexByWord(keyword, titleInLowerCase, false));
|
|||
|
|
indexOfContent = indexOfContent.concat(getIndexByWord(keyword, contentInLowerCase, false));
|
|||
|
|
});
|
|||
|
|
if (indexOfTitle.length > 0 || indexOfContent.length > 0) {
|
|||
|
|
isMatch = true;
|
|||
|
|
hitCount = indexOfTitle.length + indexOfContent.length;
|
|||
|
|
}
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
// show search results
|
|||
|
|
|
|||
|
|
if (isMatch) {
|
|||
|
|
// sort index by position of keyword
|
|||
|
|
|
|||
|
|
[indexOfTitle, indexOfContent].forEach(function (index) {
|
|||
|
|
index.sort(function (itemLeft, itemRight) {
|
|||
|
|
if (itemRight.position !== itemLeft.position) {
|
|||
|
|
return itemRight.position - itemLeft.position;
|
|||
|
|
} else {
|
|||
|
|
return itemLeft.word.length - itemRight.word.length;
|
|||
|
|
}
|
|||
|
|
});
|
|||
|
|
});
|
|||
|
|
|
|||
|
|
// merge hits into slices
|
|||
|
|
|
|||
|
|
function mergeIntoSlice(text, start, end, index) {
|
|||
|
|
var item = index[index.length - 1];
|
|||
|
|
var position = item.position;
|
|||
|
|
var word = item.word;
|
|||
|
|
var hits = [];
|
|||
|
|
var searchTextCountInSlice = 0;
|
|||
|
|
while (position + word.length <= end && index.length != 0) {
|
|||
|
|
if (word === searchText) {
|
|||
|
|
searchTextCountInSlice++;
|
|||
|
|
}
|
|||
|
|
hits.push({position: position, length: word.length});
|
|||
|
|
var wordEnd = position + word.length;
|
|||
|
|
|
|||
|
|
// move to next position of hit
|
|||
|
|
|
|||
|
|
index.pop();
|
|||
|
|
while (index.length != 0) {
|
|||
|
|
item = index[index.length - 1];
|
|||
|
|
position = item.position;
|
|||
|
|
word = item.word;
|
|||
|
|
if (wordEnd > position) {
|
|||
|
|
index.pop();
|
|||
|
|
} else {
|
|||
|
|
break;
|
|||
|
|
}
|
|||
|
|
}
|
|||
|
|
}
|
|||
|
|
searchTextCount += searchTextCountInSlice;
|
|||
|
|
return {
|
|||
|
|
hits: hits,
|
|||
|
|
start: start,
|
|||
|
|
end: end,
|
|||
|
|
searchTextCount: searchTextCountInSlice
|
|||
|
|
};
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
var slicesOfTitle = [];
|
|||
|
|
if (indexOfTitle.length != 0) {
|
|||
|
|
slicesOfTitle.push(mergeIntoSlice(title, 0, title.length, indexOfTitle));
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
var slicesOfContent = [];
|
|||
|
|
while (indexOfContent.length != 0) {
|
|||
|
|
var item = indexOfContent[indexOfContent.length - 1];
|
|||
|
|
var position = item.position;
|
|||
|
|
var word = item.word;
|
|||
|
|
// cut out 100 characters
|
|||
|
|
var start = position - 20;
|
|||
|
|
var end = position + 80;
|
|||
|
|
if(start < 0){
|
|||
|
|
start = 0;
|
|||
|
|
}
|
|||
|
|
if (end < position + word.length) {
|
|||
|
|
end = position + word.length;
|
|||
|
|
}
|
|||
|
|
if(end > content.length){
|
|||
|
|
end = content.length;
|
|||
|
|
}
|
|||
|
|
slicesOfContent.push(mergeIntoSlice(content, start, end, indexOfContent));
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
// sort slices in content by search text's count and hits' count
|
|||
|
|
|
|||
|
|
slicesOfContent.sort(function (sliceLeft, sliceRight) {
|
|||
|
|
if (sliceLeft.searchTextCount !== sliceRight.searchTextCount) {
|
|||
|
|
return sliceRight.searchTextCount - sliceLeft.searchTextCount;
|
|||
|
|
} else if (sliceLeft.hits.length !== sliceRight.hits.length) {
|
|||
|
|
return sliceRight.hits.length - sliceLeft.hits.length;
|
|||
|
|
} else {
|
|||
|
|
return sliceLeft.start - sliceRight.start;
|
|||
|
|
}
|
|||
|
|
});
|
|||
|
|
|
|||
|
|
// select top N slices in content
|
|||
|
|
|
|||
|
|
var upperBound = parseInt('1');
|
|||
|
|
if (upperBound >= 0) {
|
|||
|
|
slicesOfContent = slicesOfContent.slice(0, upperBound);
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
// highlight title and content
|
|||
|
|
|
|||
|
|
function highlightKeyword(text, slice) {
|
|||
|
|
var result = '';
|
|||
|
|
var prevEnd = slice.start;
|
|||
|
|
slice.hits.forEach(function (hit) {
|
|||
|
|
result += text.substring(prevEnd, hit.position);
|
|||
|
|
var end = hit.position + hit.length;
|
|||
|
|
result += '<b class="search-keyword">' + text.substring(hit.position, end) + '</b>';
|
|||
|
|
prevEnd = end;
|
|||
|
|
});
|
|||
|
|
result += text.substring(prevEnd, slice.end);
|
|||
|
|
return result;
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
var resultItem = '';
|
|||
|
|
|
|||
|
|
if (slicesOfTitle.length != 0) {
|
|||
|
|
resultItem += "<li><a href='" + articleUrl + "' class='search-result-title'>" + highlightKeyword(title, slicesOfTitle[0]) + "</a>";
|
|||
|
|
} else {
|
|||
|
|
resultItem += "<li><a href='" + articleUrl + "' class='search-result-title'>" + title + "</a>";
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
slicesOfContent.forEach(function (slice) {
|
|||
|
|
resultItem += "<a href='" + articleUrl + "'>" +
|
|||
|
|
"<p class=\"search-result\">" + highlightKeyword(content, slice) +
|
|||
|
|
"...</p>" + "</a>";
|
|||
|
|
});
|
|||
|
|
|
|||
|
|
resultItem += "</li>";
|
|||
|
|
resultItems.push({
|
|||
|
|
item: resultItem,
|
|||
|
|
searchTextCount: searchTextCount,
|
|||
|
|
hitCount: hitCount,
|
|||
|
|
id: resultItems.length
|
|||
|
|
});
|
|||
|
|
}
|
|||
|
|
})
|
|||
|
|
};
|
|||
|
|
if (keywords.length === 1 && keywords[0] === "") {
|
|||
|
|
resultContent.innerHTML = '<div id="no-result"><i class="fa fa-search fa-5x" /></div>'
|
|||
|
|
} else if (resultItems.length === 0) {
|
|||
|
|
resultContent.innerHTML = '<div id="no-result"><i class="fa fa-frown-o fa-5x" /></div>'
|
|||
|
|
} else {
|
|||
|
|
resultItems.sort(function (resultLeft, resultRight) {
|
|||
|
|
if (resultLeft.searchTextCount !== resultRight.searchTextCount) {
|
|||
|
|
return resultRight.searchTextCount - resultLeft.searchTextCount;
|
|||
|
|
} else if (resultLeft.hitCount !== resultRight.hitCount) {
|
|||
|
|
return resultRight.hitCount - resultLeft.hitCount;
|
|||
|
|
} else {
|
|||
|
|
return resultRight.id - resultLeft.id;
|
|||
|
|
}
|
|||
|
|
});
|
|||
|
|
var searchResultList = '<ul class=\"search-result-list\">';
|
|||
|
|
resultItems.forEach(function (result) {
|
|||
|
|
searchResultList += result.item;
|
|||
|
|
})
|
|||
|
|
searchResultList += "</ul>";
|
|||
|
|
resultContent.innerHTML = searchResultList;
|
|||
|
|
}
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
if ('auto' === 'auto') {
|
|||
|
|
input.addEventListener('input', inputEventFunction);
|
|||
|
|
} else {
|
|||
|
|
$('.search-icon').click(inputEventFunction);
|
|||
|
|
input.addEventListener('keypress', function (event) {
|
|||
|
|
if (event.keyCode === 13) {
|
|||
|
|
inputEventFunction();
|
|||
|
|
}
|
|||
|
|
});
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
// remove loading animation
|
|||
|
|
$(".local-search-pop-overlay").remove();
|
|||
|
|
$('body').css('overflow', '');
|
|||
|
|
|
|||
|
|
proceedsearch();
|
|||
|
|
}
|
|||
|
|
});
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
// handle and trigger popup window;
|
|||
|
|
$('.popup-trigger').click(function(e) {
|
|||
|
|
e.stopPropagation();
|
|||
|
|
if (isfetched === false) {
|
|||
|
|
searchFunc(path, 'local-search-input', 'local-search-result');
|
|||
|
|
} else {
|
|||
|
|
proceedsearch();
|
|||
|
|
};
|
|||
|
|
});
|
|||
|
|
|
|||
|
|
$('.popup-btn-close').click(onPopupClose);
|
|||
|
|
$('.popup').click(function(e){
|
|||
|
|
e.stopPropagation();
|
|||
|
|
});
|
|||
|
|
$(document).on('keyup', function (event) {
|
|||
|
|
var shouldDismissSearchPopup = event.which === 27 &&
|
|||
|
|
$('.search-popup').is(':visible');
|
|||
|
|
if (shouldDismissSearchPopup) {
|
|||
|
|
onPopupClose();
|
|||
|
|
}
|
|||
|
|
});
|
|||
|
|
</script>
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
<script src="https://cdn1.lncld.net/static/js/av-core-mini-0.6.4.js"></script>
|
|||
|
|
<script>AV.initialize("EWwoJgHNdlj6iBjiFlMcabUO-gzGzoHsz", "x8FxDrYG79C8YFrTww9ljo8K");</script>
|
|||
|
|
<script>
|
|||
|
|
function showTime(Counter) {
|
|||
|
|
var query = new AV.Query(Counter);
|
|||
|
|
var entries = [];
|
|||
|
|
var $visitors = $(".leancloud_visitors");
|
|||
|
|
|
|||
|
|
$visitors.each(function () {
|
|||
|
|
entries.push( $(this).attr("id").trim() );
|
|||
|
|
});
|
|||
|
|
|
|||
|
|
query.containedIn('url', entries);
|
|||
|
|
query.find()
|
|||
|
|
.done(function (results) {
|
|||
|
|
var COUNT_CONTAINER_REF = '.leancloud-visitors-count';
|
|||
|
|
|
|||
|
|
if (results.length === 0) {
|
|||
|
|
$visitors.find(COUNT_CONTAINER_REF).text(0);
|
|||
|
|
return;
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
for (var i = 0; i < results.length; i++) {
|
|||
|
|
var item = results[i];
|
|||
|
|
var url = item.get('url');
|
|||
|
|
var time = item.get('time');
|
|||
|
|
var element = document.getElementById(url);
|
|||
|
|
|
|||
|
|
$(element).find(COUNT_CONTAINER_REF).text(time);
|
|||
|
|
}
|
|||
|
|
for(var i = 0; i < entries.length; i++) {
|
|||
|
|
var url = entries[i];
|
|||
|
|
var element = document.getElementById(url);
|
|||
|
|
var countSpan = $(element).find(COUNT_CONTAINER_REF);
|
|||
|
|
if( countSpan.text() == '') {
|
|||
|
|
countSpan.text(0);
|
|||
|
|
}
|
|||
|
|
}
|
|||
|
|
})
|
|||
|
|
.fail(function (object, error) {
|
|||
|
|
console.log("Error: " + error.code + " " + error.message);
|
|||
|
|
});
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
function addCount(Counter) {
|
|||
|
|
var $visitors = $(".leancloud_visitors");
|
|||
|
|
var url = $visitors.attr('id').trim();
|
|||
|
|
var title = $visitors.attr('data-flag-title').trim();
|
|||
|
|
var query = new AV.Query(Counter);
|
|||
|
|
|
|||
|
|
query.equalTo("url", url);
|
|||
|
|
query.find({
|
|||
|
|
success: function(results) {
|
|||
|
|
if (results.length > 0) {
|
|||
|
|
var counter = results[0];
|
|||
|
|
counter.fetchWhenSave(true);
|
|||
|
|
counter.increment("time");
|
|||
|
|
counter.save(null, {
|
|||
|
|
success: function(counter) {
|
|||
|
|
var $element = $(document.getElementById(url));
|
|||
|
|
$element.find('.leancloud-visitors-count').text(counter.get('time'));
|
|||
|
|
},
|
|||
|
|
error: function(counter, error) {
|
|||
|
|
console.log('Failed to save Visitor num, with error message: ' + error.message);
|
|||
|
|
}
|
|||
|
|
});
|
|||
|
|
} else {
|
|||
|
|
var newcounter = new Counter();
|
|||
|
|
/* Set ACL */
|
|||
|
|
var acl = new AV.ACL();
|
|||
|
|
acl.setPublicReadAccess(true);
|
|||
|
|
acl.setPublicWriteAccess(true);
|
|||
|
|
newcounter.setACL(acl);
|
|||
|
|
/* End Set ACL */
|
|||
|
|
newcounter.set("title", title);
|
|||
|
|
newcounter.set("url", url);
|
|||
|
|
newcounter.set("time", 1);
|
|||
|
|
newcounter.save(null, {
|
|||
|
|
success: function(newcounter) {
|
|||
|
|
var $element = $(document.getElementById(url));
|
|||
|
|
$element.find('.leancloud-visitors-count').text(newcounter.get('time'));
|
|||
|
|
},
|
|||
|
|
error: function(newcounter, error) {
|
|||
|
|
console.log('Failed to create');
|
|||
|
|
}
|
|||
|
|
});
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
error: function(error) {
|
|||
|
|
console.log('Error:' + error.code + " " + error.message);
|
|||
|
|
}
|
|||
|
|
});
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
$(function() {
|
|||
|
|
var Counter = AV.Object.extend("Counter");
|
|||
|
|
if ($('.leancloud_visitors').length == 1) {
|
|||
|
|
addCount(Counter);
|
|||
|
|
} else if ($('.post-title-link').length > 1) {
|
|||
|
|
showTime(Counter);
|
|||
|
|
}
|
|||
|
|
});
|
|||
|
|
</script>
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
<script>
|
|||
|
|
(function(){
|
|||
|
|
var bp = document.createElement('script');
|
|||
|
|
var curProtocol = window.location.protocol.split(':')[0];
|
|||
|
|
if (curProtocol === 'https') {
|
|||
|
|
bp.src = 'https://zz.bdstatic.com/linksubmit/push.js';
|
|||
|
|
}
|
|||
|
|
else {
|
|||
|
|
bp.src = 'http://push.zhanzhang.baidu.com/push.js';
|
|||
|
|
}
|
|||
|
|
var s = document.getElementsByTagName("script")[0];
|
|||
|
|
s.parentNode.insertBefore(bp, s);
|
|||
|
|
})();
|
|||
|
|
</script>
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
|
|||
|
|
</body>
|
|||
|
|
</html>
|