计算机科学 ›› 2019, Vol. 46 ›› Issue (6A): 41-44.

• 综述研究 • 上一篇    下一篇

屏幕防窃拍方法综述

王晓媛, 张文涛   

  1. 中国航天系统科学与工程研究院 北京100037
  • 出版日期:2019-06-14 发布日期:2019-07-02
  • 作者简介:王晓媛(1993-),女,硕士生,主要研究方向为信息安全,E-mail:wxy13381216098@163.com;张文涛(1971-),男,硕士,研究员,主要研究方向为信息安全。

Overview of Preventing Candid Photos Methods for Electronic Screens

WANG Xiao-yuan, ZHANG Wen-tao   

  1. China Aerospace Academy of Systems Science and Engineering,Beijing 100037,China
  • Online:2019-06-14 Published:2019-07-02

摘要: 如今,手机等设备的拍照性能愈发强大,其在给人们的生活带来便捷和快乐的同时,也为不法分子窃取企业商业秘密乃至国家秘密降低了犯罪成本,便捷而隐蔽的窃密方式给信息安全的防范工作带来了极大挑战。针对屏幕防窃拍方法,文中基于已有的相关学术研究和商业方案,介绍了3类屏幕防窃拍方法,分别为信息隐藏显示法、摄像头检测法和屏幕水印法,从信息安全防护角度分析了各类方法的特征、优势与限制。基于各类方法的局限性,最后提出了基于计算机视觉的新解决思路。

关键词: 防窃拍方法, 计算机视觉, 屏幕水印, 摄像头检测, 信息隐藏显示

Abstract: Nowadays,the performance of mobile phones and other devices has become more and more powerful.It brings convenience and entertainment to people’s life.At the same time,it also reduces the cost of crime to steal business secrets even national secrets.The convenient and covert ways of stealing secrets have brought great challenges to information security.According to existing academic research and business solutions,this paper introduced three kinds of methods:hiding display information,detection camera and screen watermarking.Then it analyzed the characteristics,advantages and limitations of various methods from the angle of information security protection.Finally,a new solution based on computer vision was proposed to avoid the limitations.

Key words: Computer vision, Detection camera, Hiding display information, Preventing candid photos methods, Screen watermark

中图分类号: 

  • TP30
[1]朱杰.美国NSA全球监听和网络窃密行径深度揭秘 看山姆大叔如何玩转“全球监听”[J].中国信息安全,2014(6):80-87.
[2]Risk Based Security.Data Breach Quick-View:An Executice’s Guide to 2013 Data Breach Trends[OL].https://pages.riskbasedsecurity.com/hubfs/Reports/2016_MidYear_DataBreachQuickViewReport.pdf.
[3]范荣.从黄宇间谍窃密案谈加强保密管理对策[J].保密工作,2016(5):40-42.
[4]赵飞.智能手机泄密风险分析及安全保密技术方案[J].电子技术与软件工程,2017(2):216.
[5]ROESSLER M.How to find hidden cameras[OL].http://www.doc88.com/p-9641502582457.html.
[6]TRUONG K N,PATEL S N,SUMMET J W,et al.Preventing camera recording by designing a capture-resistant environment[C]∥Proceedings of the 7th International Conference on Ubiquitous Computing.Tokyo,Berlin-Heidelberg:Springer,2005.
[7]GROSGES T.Retro-reflection of glass beads for traffic road stripe paints[J].Optical Materials,2008,30(10):1549-1554.
[8]YAMADA T,GOHSHI S,ECHIZEN I.Countermeasure of reshooting prevention against attack with infrared-cut filter[C]∥Proc.of IPSJ Symposium on Computer Security(CSS).2010.
[9]MAHDAVI M,MAHDAVI H,FARSI F.System and method for video recording device detection:US,20120128330 [EB/OL].(2012-05-24) [2012-11-15].http://www.faqs.org/patents/app/20120128330.
[10]FUJIKAWA M,AKIMOTO J,ODA F,et al.Study of Countermeasures for Content Leaks by Video Recording[C]∥2011 Sixth International Conference on Availability,Reliability and Security.2011.
[11]GURI M,HASSON O,KEDMA G,et al.An Optical Covert-Channel to Leak Data through an Air-Gap[OL].https://arxiv.org/pdf/1607.03946.pdf.
[12]HUANG H C,FANG W C.Metadata-based image watermar-king for copyright protection[J].Simulation Modeling Practice and Theory,2010,18(4):436-445.
[13]JUNG E H,CHO S Y.A robust digital watermarking system adopting 2d barcode against digital piracy on p2p network[J].IJCSNS International Journal of Computer Science and Network Security,2006,6(10):263.
[14]PIEC M,RAUBER A.Real-Time Screen Watermarking Using Overlaying Layer[C]∥Ninth International Conference on Availability.2014.
[15]耿振民,王衍江.一种防止对屏幕拍照的反泄密方法:CN 103390141 A[P].2013.
[16]张文豪,吴怀宇.基于摄像头检测的防盗拍系统开发和算法研究[J].电子设计工程,2013,21(18):48-52.
[17]汪嘉恒,程雨诗,徐文渊.基于辐射特征的隐藏摄像头检测技术[J].工业控制计算机,2017,30(2):50-52.
[18]汪嘉恒.面向防拍摄的摄像检测技术[D].杭州:浙江大学,2017.
[19]褚晶辉,田叶,苏育挺.基于频率约束的相机与屏幕通信隐写算法[J].激光与光电子学进展,2018,55:051003.
[20]四种屏幕防拍照、截屏、打印等数据泄露水印解决方案[OL].https://www.leagsoft.com/doc/article/1416.html.
[21]防范屏幕拍照泄密不再束手无策[OL].http://www.ip-guard.net/blog/?p=1922.
[22]吴海涛,詹永照.数字水印技术综述[J].软件导刊,2015,14(8):45-49.
[23]吴亚坤,邸春红.数字水印技术综述[J].辽宁大学学报(自然科学版),2010,37(3):202-206.
[24]马颖颖.数字水印攻击方法的一些研究[D].杭州:杭州电子科技大学,2011.
[25]李彦冬.基于卷积神经网络的计算机视觉关键技术研究[D].成都:电子科技大学,2017.
[26]杨益平,闵啸.基于计算机视觉的手势识别人机交互技术[J].电子技术与软件工程,2018(12):138-139.
[1] 张继凯, 李琦, 王月明, 吕晓琪.
基于单目RGB图像的三维手势跟踪算法综述
Survey of 3D Gesture Tracking Algorithms Based on Monocular RGB Images
计算机科学, 2022, 49(4): 174-187. https://doi.org/10.11896/jsjkx.210700084
[2] 谈馨悦, 何小海, 王正勇, 罗晓东, 卿粼波.
基于Transformer交叉注意力的文本生成图像技术
Text-to-Image Generation Technology Based on Transformer Cross Attention
计算机科学, 2022, 49(2): 107-115. https://doi.org/10.11896/jsjkx.210600085
[3] 干创, 吴桂兴, 詹庆原, 王鹏焜, 彭志磊.
基于骨架模态的多级门控图卷积动作识别网络
Multi-scale Gated Graph Convolutional Network for Skeleton-based Action Recognition
计算机科学, 2022, 49(1): 181-186. https://doi.org/10.11896/jsjkx.201100164
[4] 冯芙蓉, 张兆功.
目标轮廓检测技术新进展
Recent Advances for Object Contour Detection Technology
计算机科学, 2021, 48(6A): 1-9. https://doi.org/10.11896/jsjkx.201000044
[5] 张开华, 樊佳庆, 刘青山.
视觉目标跟踪十年研究进展
Advances on Visual Object Tracking in Past Decade
计算机科学, 2021, 48(3): 40-49. https://doi.org/10.11896/jsjkx.201100186
[6] 李亚泽, 刘宏哲.
基于相邻特征融合的目标检测
Object Detection Based on Neighbour Feature Fusion
计算机科学, 2021, 48(12): 264-268. https://doi.org/10.11896/jsjkx.201200196
[7] 程铭, 马佩, 何儒汉.
基于流形结构神经网络的服装图像集分类方法
Clothing Image Sets Classification Based on Manifold Structure Neural Network
计算机科学, 2021, 48(11A): 391-395. https://doi.org/10.11896/jsjkx.201200127
[8] 陈浩楠, 雷印杰, 王浩.
基于行列解耦采样的轻量车道线检测模型
Lightweight Lane Detection Model Based on Row-column Decoupled Sampling
计算机科学, 2021, 48(11A): 416-419. https://doi.org/10.11896/jsjkx.201100206
[9] 谢海平, 李高源, 杨海涛, 赵洪利.
超分辨率重构遥感图像分类研究
Classification Research of Remote Sensing Image Based on Super Resolution Reconstruction
计算机科学, 2021, 48(11A): 424-428. https://doi.org/10.11896/jsjkx.210300132
[10] 何鑫, 许娟, 金莹莹.
行为关联网络:完整的变化行为建模
Action-related Network:Towards Modeling Complete Changeable Action
计算机科学, 2020, 47(9): 123-128. https://doi.org/10.161896/jsjkx.190800101
[11] 李泽文, 李子铭, 费天禄, 王瑞琳, 谢在鹏.
基于残差生成对抗网络的人脸图像复原
Face Image Restoration Based on Residual Generative Adversarial Network
计算机科学, 2020, 47(6A): 230-236. https://doi.org/10.11896/JsJkx.190400118
[12] 张鹏, 宋一凡, 宗立波, 刘立波.
3D目标检测进展综述
Advances in 3D Object Detection:A Brief Survey
计算机科学, 2020, 47(4): 94-102. https://doi.org/10.11896/jsjkx.190400142
[13] 苗益, 赵增顺, 杨雨露, 徐宁, 杨皓然, 孙骞.
图像描述技术综述
Survey of Image Captioning Methods
计算机科学, 2020, 47(12): 149-160. https://doi.org/10.11896/jsjkx.200500039
[14] 李煌, 王晓莉, 项欣光.
基于文本三区域分割的场景文本检测方法
Scene Text Detection Based on Triple Segmentation
计算机科学, 2020, 47(11): 142-147. https://doi.org/10.11896/jsjkx.200800157
[15] 刘剑, 金泽群.
基于深度学习的人脸表情迁移方法
Facial Expression Transfer Method Based on Deep Learning
计算机科学, 2019, 46(6A): 250-253.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!