物联网安全研究综述：威胁、检测与防御

doi:10.11959/j.issn.1000-436x.2021124

Abstract

Abstract:

Based on the IoT security literatures published in the international conferences on network security (ACM CCS, USENIX Security, NDSS, IEEE S＆amp;P) in recent five years, and other prominent researches, the works from the perspective of ＆quot;threat, detection, defense＆quot; were systematically summarized and analyzed.Firstly the basic architecture of the IoT system was introduced.Then the main threats proposed in these works were classified into eight categories, and the causes and hazards of the threats were analyzed.After that, six detection and five defense schemes against these threats were introduced, and their technical principles, advantages and disadvantages were compared.At last, on the basis of the above analysis, the main challenges that the current research still faces were put forward, and the research directions of future works were point out.

Key words: IoT, security, threat, detection, defense

CLC Number:

TP391.44

Yiyu YANG, Wei ZHOU, Shangru ZHAO, Cong LIU, Yuhui ZHANG, He WANG, Wenjie WANG, Yuqing ZHANG. Survey of IoT security research: threats, detection and defense[J]. Journal on Communications, 2021, 42(8): 188-205.

Figures/Tables 10

References 110

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威胁类型	漏洞成因	主要危害	文献	文献数量/篇
云平台访问控制缺陷	授权粒度过粗，授权标准不对称	越权控制、事件窃听、隐私泄露	文献[8-11]	4
云平台恶意应用	恶意用户上传应用，应用审核机制不完善	隐私泄露、非法控制	文献[4,9,12-17]	8
云平台实体和应用交互漏洞	实体和应用交互复杂，执行冲突难以检测	设备劫持、拒绝服务、隐私泄露	文献[13-14,18-20]	5
通信协议漏洞	协议缺乏内建安全机制，厂商忽略安全因素	拒绝服务、设备劫持、重放攻击、隐私泄露	文献[18-19,21-27]	9
通信流量侧信道信息泄露	物联网通信流量具有突出特征	隐私泄露	文献[28-33]	6
设备固件漏洞	有限的计算和存储资源，缺乏有效检测工具，缺乏内存和权限管理	系统崩溃、保护绕过、恶意命令、隐私泄露	文献[34-41]	8
基于语音信道的攻击	藏匿在语音信道中的命令	越权控制、隐私泄露	文献[42-47]	6
基于物联网设备的僵尸网络	设备规模庞大，设备漏洞广泛存在	大规模拒绝服务、恶意软件分发	文献[48-50]	3

文献	采用特征	识别方法	攻击效果
文献[28]	Wi-Fi信号强度	Wi-Fi多路信号传播波动模型	①
文献[29]	端口号、负载大小、TCP窗口值等	CNN（convolutional neural network）+RNN（recurrent neural network）	①②
文献[30]	DNS查询目标、NTP请求数、SSL/TLS加密套件	朴素贝叶斯多项式分类和随机森林	①②
文献[31]	方向、包长、发包时间间隔平均值和标准差	随机森林、DBSCAN（density-based spatial clustering of applications with noise）	①②③④
文献[32]	包长平均值和方差、时间间隔平均值、tsfresh和特征工程提取的特征	k近邻、随机森林、隐式马尔可夫模型	①②③④⑤
文献[33]	方向和包长	DBSCAN	①②③④⑤
注：①判断设备/目标存在，②识别设备类型，③判断设备事件发生，④识别事件，⑤推断用户行为

检测方案	面向威胁类型	主要技术原理	主要优点	主要缺点	文献	文献数量/篇
云平台恶意应用检测	云平台恶意应用	基于敏感信息的数据流追踪，语音黑盒测试	自动化、大规模检测，有效识别恶意应用	依赖平台特性	文献[4,12, 15-16, 52-54]	7
云平台实体和应用交互漏洞检测	云平台实体和应用交互漏洞	模型检测	识别实体交互复杂过程中的逻辑漏洞	需要人工分析，且对交互解析的方法存在局限性	文献[13-14, 18-20, 55]	6
基于静态分析的固件漏洞检测	设备固件漏洞、基于物联网设备的僵尸网络	符号执行，污点分析，二进制相似性比较	自动化检测固件漏洞	对编译优化和混淆敏感，固件难以获取和自动加载	文献[39-40,42, 56-60]	8
基于动态分析的固件漏洞检测	设备固件漏洞、基于物联网设备的僵尸网络	基于 QEMU（quick Emulator）仿真，推断外设输入	动态调试、准确识别漏洞原因和位置	需要人工分析，面向有限固件类型，仿真效果受限	文献[40, 61-68]	9
基于手机 App 的固件漏洞检测	设备固件漏洞	基于App的模糊测试，App代码相似性分析	不用分析设备和解析固件	需要设备拥有对应App，App 与设备较强的关联性	文献[69-72]	4
基于侧信道的设备异常检测	设备固件漏洞、基于物联网设备的僵尸网络	基于流量特征，基于物理特征，环境上下文特征	识别设备异常行为、非侵入式方案	容易受到信号强弱、协议类型和通信模式的影响，对设备环境有要求	文献[73-80]	8

文献	建模方式和检测方法	检测平台	检测效果
文献[13]	通过解析源代码得到多个应用状态转换模型组合，基于安全策略检测动作冲突	SmartThings	在28种SmartApp组合中识别出3种组合违背11项安全策略
文献[14]	通过代码插桩在运行过程中动态建立多个应用状态转换模型，基于安全策略检测动作冲突	SmartThings、IFTTT	在 16个 SmartApp和 9个 Applet的组合中识别出3种组合违背9项安全策略
文献[20]	基于自然语言处理建立自动执行规则之间的交互模型，基于SMT求解技术检测规则间漏洞	IFTTT	在31.5万个Applet应用中，根据安装数量组成可信的规则集，发现规则集中66%具有交互漏洞
文献[55]	通过解析应用源代码和文本描述，建立应用之间通过共同物理信道连接的动作模型，基于不同物理信道的风险值计算应用组合风险	SmartThings	在185个SmartApp中发现162种基于共同物理信道的隐式关联，其中37种关联可能产生安全隐患

防御方案	面向威胁类型	主要技术原理	主要优点	主要缺点	文献	文献数量/篇
细粒度的云平台访问控制	云平台访问控制缺陷	提升权限管理粒度	有效识别越权操作，弥补平台审核机制不足	依赖平台特性，需要用户参与	文献[10, 83-87]	6
安全的通信协议	通信协议漏洞	增加内在安全机制，设计新型配对协议	增强协议机密性和完整性	安全配对协议需要感知装置支持，邻近设备不完全可信	文献[21, 88-94]	8
流量特征隐藏	通信流量侧信道信息泄露	数据包封装，流量塑形	有效对抗侧信道信息泄露	增加通信时延和负载，增加流量噪声	文献[30, 32-33, 75, 95-96]	6
基于可信计算的固件安全防护机制	设备固件漏洞、基于物联网设备的僵尸网络	程序组件权限和内存地址空间隔离，控制流完整性保护，远程认证	有效防御传统固件漏洞，大规模管理中有效发现异常设备，设备自组网络安全运行	性能和适用面需要进一步提升，细粒度的控制流认证影响系统实时性	文献[34, 37-38, 97-101]	8
语音攻击防御	基于语音信道的攻击	安全提示和语音确认，声纹识别，信号过滤	有效阻止藏匿的恶意语音命令	面临可用性和成本的额外开销	文献[42-45, 102]	5

Survey of IoT security research: threats, detection and defense

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文献	技术原理	主要特点	性能开销
文献[34]	组件权限和内存地址空间隔离	识别与分离特权指令，实现栈保护、代码和数据区域隔离，无法实现进程级别的代码隔离	平均增加1.8%执行时间和0.5%能耗
文献[97]	组件权限和内存地址空间隔离	基于 MPU 实现进程内存空间的隔离，但是划分进程内数据与代码区域的方法不灵活	最高可减少93%进程内存空间
文献[98]	组件权限和内存地址空间隔离	对固件执行单元进行更细粒度的权限划分，基于定制的安全策略对分离的组件灵活实施最小权限模型	最高引入13%的运行开销，比现有技术减少59%的Flash占用，减少84%的内存占用
文献[37]	控制流完整性保护	将函数的有效返回地址集合放到不可写的内存区域中，不需要特殊硬件模块支持	平均运行开销只有0.1%，内存开销可忽略，平均增加54.1%的Flash占用
文献[38]	控制流完整性保护	基于“影子栈”技术，配置内存保护单元来实施内存访问规则，确保程序返回到合法目标地址	平均增加1.3%和3.4%的性能开销，以及8.9%和2.3%的代码体积

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