基于智能手表运动传感器的新型攻击及其防范

宋晨光; 刘建伟; 伍前红; 关振宇

doi:10.11959/j.issn.1000-436x.2015304

您当前的位置：

首页 >

文章列表页 >

基于智能手表运动传感器的新型攻击及其防范

学术通信 | 更新时间：2024-06-05

- 基于智能手表运动传感器的新型攻击及其防范
- New attack based on smartwatch motion sensors and the protection method research
- 通信学报 2015年36卷第Z1期页码：235-242
- 作者机构：
  
  北京航空航天大学电子信息工程学院，北京 100191
- 作者简介：
  
  [ "宋晨光（1993-），男，河南驻马唐人，北京航空航天大学硕士生，主要研究方向为可穿戴设备安全、网络与信息安全。" ]
  [ "刘建伟（1964-），男，山东莱州人，北京航空航天大学教授、博士生导师，主要研究方向为密码学、网络与信息安全。" ]
  [ "伍前红（1973-），男，四川安岳人，北京航空航天大学教授、博士生导师，主要研究方向为密码学、信息安全、计算安全。" ]
  [ "关振宇（1984-），男，辽宁盘锦人，北京航空航天大学讲师，主要研究方向为空间网络安全、信息安全和密码学。" ]
- 基金信息：
  
  国家重点基础研究发展计划（“973”计划）基金资助项目(2012CB315905);国家自然科学基金资助项目(61272501);国家自然科学基金资助项目(61370190);国家自然科学基金资助项目(61173154);中央高校基本科研业务费专项基金资助项目(YWF-15-GJSYS-059)
- DOI：10.11959/j.issn.1000-436x.2015304
  中图分类号： TP309
- 网络出版日期：2015-11，
  
  纸质出版日期：2015-11-25
- 稿件说明：
移动端阅览
宋晨光, 刘建伟, 伍前红, 等. 基于智能手表运动传感器的新型攻击及其防范[J]. 通信学报, 2015,36(Z1):235-242.

Chen-guang SONG, Jian-wei LIU, Qian-hong WU, et al. New attack based on smartwatch motion sensors and the protection method research[J]. Journal on communications, 2015, 36(Z1): 235-242.
宋晨光, 刘建伟, 伍前红, 等. 基于智能手表运动传感器的新型攻击及其防范[J]. 通信学报, 2015,36(Z1):235-242. DOI： 10.11959/j.issn.1000-436x.2015304.

Chen-guang SONG, Jian-wei LIU, Qian-hong WU, et al. New attack based on smartwatch motion sensors and the protection method research[J]. Journal on communications, 2015, 36(Z1): 235-242. DOI： 10.11959/j.issn.1000-436x.2015304.

摘要

智能手表上搭载了加速度计、陀螺仪等运动传感器，且会随着手部运动而产生位移，使通过智能手表窃取用户外部键盘输入成为了可能。研究了智能设备上基于6轴加速度计/陀螺仪来推断用户键盘输入的可行性，建立了用户进行键盘输入时的运动模型来对手部运动进行分类识别。当用户执行敏感输入，如在数字键盘上输入密码时，可根据传感器信息推断出密码。经实验验证，该方法可有效识别4位PIN码，证明此安全问题值得人们重视。

Abstract

Smart watch shipped with various embedded motion sensors

such as the accelerometer and gyroscope.Smart watch can follow the movement of hand to recognize the corresponding displacement

so that others can steal user’s external keyboard input through smart watches.The feasibility of intelligent device based on 6 axis accelerometer/gyroscope to infer the user’s keyboard input was researched

and the user’s keyboard input kinematic model for motion classification recognition was established.When users perform sensitive inputting

such as passwords inputting on digital keyboard

the passwords according to sensor information can be deduced.The results show that the approach can effectively recognize the PIN code on keyboard

which absolutely prove the seriousness of this safety problem.

关键词

Keywords

references

CHIN E , FELT A P , SEKAR V , et al . Measuring user confidence in smartphone security and privacy [A ] . Proceedings of the Eighth Symposium on Usable Privacy and SecurityACM [C ] . 2012 .

JEON W , KIM J , LEE Y , et al . A practical analysis of smartphone security [J ] . Lecture Notes in Computer Science , 2011 , 6771 : 311 - 320 .

WU L , DU X , FU X . Security threats to mobile multimedia applications:camera-based attacks on mobile phones [J ] . IEEE Communications Magazine , 2014 , 52 ( 3 ): 80 - 87 .

Google . Android Sensors [EB/OL ] . http://developer.android.com/reference/android/hardware/SensorEvent.html http://developer.android.com/reference/android/hardware/SensorEvent.html . 2015 .

MARQUARDT P , VERMA A , CARTER H , et al . (sp)iPhone:decoding vibrations from nearby keyboards using mobile phone accelerometers [A ] . Proceedings of ACM CCS [C ] . 2011 . 551 - 562 .

CAI L , CHEN H . Touchlogger:inferring keystrokes on touch screen from smartphone motion [A ] . HotSec’11 Proceedings of the 6th USENIX Conference on Hot Topics in Security [C ] . 2011 . 9 .

XU Z , BAI K , ZHU S . Taplogger:inferring user inputs on smartphone touchscreens using on-board motion sensors [A ] . Proceedings of the Fifth Acm Conference on Wireless Network Security [C ] . 2012 . 113 - 124 .

Apple . Apple Pay [EB/OL ] . http://www.apple.com/apple-pay/ http://www.apple.com/apple-pay/ . 2015 .

KELA J , KORPIPÄÄ P , MÄNTYJÄRVI J , et al . Accelerometer-based gesture control for a design environment [J ] . Personal and Ubiquitous Computing , 2006 , 10 ( 5 ): 285 - 299 .

乔相伟 . 基于四元数非线性滤波的飞行器姿态确定算法研究 [D ] . 哈尔滨工程大学 , 2011 .

QIAO X W . Attitude Determination Algorithm Based on Quaternion Nonlinear Filter for Spacecraft [D ] . Harbin Engineering University , 2011 .

KOWNACKI C . Optimization approach to adapt Kalman filters for the real-time application of accelerometer and gyroscope signals' filtering [J ] . Digital Signal Processing , 2011 , 21 ( 1 ): 131 - 140 .

TRAWNY N , ROUMELIOTIS S I . Indirect Kalman filter for 3D pose estimation [J ] . University of Minnesota,Dept.of Comp.Sci.＆ Eng.,Tech.Rep , 2005 , 2 .

张春莹 , 潘荣江 . 由整体到局部的平面曲线部分匹配算法 [J ] . 计算机辅助设计与图形学学报 , 2008 ,( 7 ): 894 - 899 .

ZHANG C Y , PAN R J . A global to local partial matching algorithm for planar curves [J ] . Journal of Computer-Aided Design ＆ Computer Graphics , 2008 ,( 7 ): 894 - 899 .

CHEN F S , FU C M , HUANG C L . Hand gesture recognition using a real-time tracking method and hidden Markov models [J ] . Image and vision computing , 2003 , 21 ( 8 ): 745 - 758 .

ZHOU S , SHAN Q , FEI F , et al . Gesture recognition for interactive controllers using MEMS motion sensors [A ] . Nano/Micro Engineered and Molecular Systems,NEMS 2009.4th IEEE International Conference [C ] . IEEE , 2009 . 935 - 940 .

FINK G A . Markov Models for Pattern Recognition:from Theory to Applications [M ] . Springer Science ＆ Business Media , 2014 .

KRIZHEVSKY A , SUTSKEVER I , HINTON G E . Imagenet classification with deep convolutional neural networks [A ] . Advances in Neural Information Processing Systems [C ] . 2012 . 1097 - 1105 .

高鹏毅 . BP 神经网络分类器优化技术研究 [D ] . 武汉:华中科技大学 , 2012 .

GAO P Y . Study on the Optimization of Backpropagation Neural Network Classifier [D ] . Wuhan:Huazhong University of Science and Technology , 2012 .

SHIRAKAWA K , SHIMIZ M , OKUBO N , et al . A large-signal characterization of an HEMT using a multilayered neural network [J ] . Journal of Henan University , 2011 , 45 ( 9 ): 1630 - 1633 .

张毅 . 静态手势识别的神经网络方法研究 [D ] . 成都:电子科技大学 , 2011 .

ZHANG Y . Study on Neural Network for Static Gesture Recogni-tion [D ] . Chengdu:University of Electronic Science and Technology of China , 2011 .

Google . Android Motion sensors [EB/OL ] . http://developer.android.com/guide/topics/sensors/sensors_motion.html http://developer.android.com/guide/topics/sensors/sensors_motion.html , 2015 .

InvenSense . 6-Axis Motion Sensors [EB/OL ] . http://www.invensense.com/products/motion-tracking/6-axis/ http://www.invensense.com/products/motion-tracking/6-axis/ . 2015 .

浏览量

1279

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据