Please wait a minute...
Front. Inform. Technol. Electron. Eng.  2014, Vol. 15 Issue (6): 435-444    DOI: 10.1631/jzus.C1300262
    
静态视觉图像全加密与选择加密性能比较研究
Osama A. Khashan, Abdullah M. Zin, Elankovan A. Sundararajan
Centre for Software Technology and Management, Faculty of Information Science and Technology, National University of Malaysia (UKM), Bangi 43600, Selangor, Malaysia
Performance study of selective encryption in comparison to full encryption for still visual images
Osama A. Khashan, Abdullah M. Zin, Elankovan A. Sundararajan
Centre for Software Technology and Management, Faculty of Information Science and Technology, National University of Malaysia (UKM), Bangi 43600, Selangor, Malaysia
 全文: PDF 
摘要: 研究目的:安全图像的广泛使用,使得数字图像安全防护成为信息安全领域的一个重要关注点。图像加密是保障机密、保护隐私最为有效的方法。然而,数字图像的大尺寸和复杂结构,使得图像全加密耗费巨大计算量和处理时间,不利于其在实时系统中频繁使用。因此,许多近期研究采用选择加密,只对图像重要部分加密,以降低加密成本。相比全加密,选择加密性能如何?有必要加以评估。
研究方法:本文研究了选择加密方法中运用的图像分割方法(如边缘检测和人脸检测)在视觉图像重要部分判定上的性能和效率。通过实验,对采用对称加密算法的选择加密和全加密的运算结果进行比较。
重要结论:实验结果证实,较之全加密,基于边缘和人脸检测的选择加密方法显著减少静态视觉图像的加密时间。选择加密适合于对安全等级有适当要求的实时应用。
关键词: 选择性图像加密边缘检测人脸检测    
Abstract: Securing digital images is becoming an important concern in today’s information security due to the extensive use of secure images that are either transmitted over a network or stored on disks. Image encryption is the most effective way to fulfil confidentiality and protect the privacy of images. Nevertheless, owing to the large size and complex structure of digital images, the computational overhead and processing time needed to carry out full image encryption prove to be limiting factors that inhibit it of being used more heavily in real time. To solve this problem, many recent studies use the selective encryption approach to encrypt significant parts of images with a hope to reduce the encryption overhead. However, it is necessary to realistically evaluate its performance compared to full encryption. In this paper, we study the performance and efficiency of image segmentation methods used in the selective encryption approach, such as edges and face detection methods, in determining the most important parts of visual images. Experiments were performed to analyse the computational results obtained by selective image encryption compared to full image encryption using symmetric encryption algorithms. Experiment results have proven that the selective encryption approach based on edge and face detection can significantly reduce the time of encrypting still visual images as compared to full encryption. Thus, this approach can be considered a good alternative in the implementation of real-time applications that require adequate security levels.
Key words: Selective image encryption    Edge detection    Face detection
收稿日期: 2013-09-18 出版日期: 2014-06-06
CLC:  TP309  
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
Osama A. Khashan
Abdullah M. Zin
Elankovan A. Sundararajan

引用本文:

Osama A. Khashan, Abdullah M. Zin, Elankovan A. Sundararajan. Performance study of selective encryption in comparison to full encryption for still visual images. Front. Inform. Technol. Electron. Eng., 2014, 15(6): 435-444.

链接本文:

http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.C1300262        http://www.zjujournals.com/xueshu/fitee/CN/Y2014/V15/I6/435

[1] Ehsan Saeedi, Yinan Kong, Md. Selim Hossain. 边信道攻击和学习向量量化[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(4): 511-518.
[2] Yu-jun Xiao, Wen-yuan Xu, Zhen-hua Jia, Zhuo-ran Ma, Dong-lian Qi. 一种非侵入式的基于功耗的可编程逻辑控制器异常检测方案[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(4): 519-534.
[3] Gaurav Bansod, Narayan Pisharoty, Abhijit Patil. BORON:面向普适计算的超轻量低功耗加密设计[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(3): 332-345.
[4] Feng-he Wang, Chun-xiao Wang, Zhen-hua Liu. 标准模型下基于高效分级身份的格上加密方案[J]. Front. Inform. Technol. Electron. Eng., 2016, 17(8): 781-791.
[5] Jia Xie, Yu-pu Hu, Jun-tao Gao, Wen Gao. NTRU格上基于身份签名的高效方案[J]. Front. Inform. Technol. Electron. Eng., 2016, 17(2): 135-142.
[6] Kok-Seng Wong, Myung Ho Kim. 面向优选应答的k-匿名模型[J]. Front. Inform. Technol. Electron. Eng., 2015, 16(9): 720-731.
[7] Kuo-Hui Yeh. 一套具备使用者不可追踪性的轻量化身分鉴别机制[J]. Front. Inform. Technol. Electron. Eng., 2015, 16(4): 259-271.
[8] Osama A. Khashan, Abdullah M. Zin, Elankovan A. Sundararajan. ImgFS:一种利用用户空间文件系统的图片存储透明加密技术[J]. Front. Inform. Technol. Electron. Eng., 2015, 16(1): 28-42.
[9] Shuang Tan, Yan Jia. NaEPASC:一种新颖且高效的云数据公开审计机制[J]. Front. Inform. Technol. Electron. Eng., 2014, 15(9): 794-804.
[10] Kuo-Hui Yeh, Kuo-Yu Tsai, Jia-Li Hou. Analysis and design of a smart card based authentication protocol[J]. Front. Inform. Technol. Electron. Eng., 2013, 14(12): 909-917.
[11] Yong Cheng, Zhi-ying Wang, Jun Ma, Jiang-jiang Wu, Song-zhu Mei, Jiang-chun Ren. [J]. Frontiers of Information Technology & Electronic Engineering, 2013, 14(2): 85-97.
[12] Hong-yuan Chen, Yue-sheng Zhu. A robust watermarking algorithm based on QR factorization and DCT using quantization index modulation technique[J]. Front. Inform. Technol. Electron. Eng., 2012, 13(8): 573-584.
[13] Baiying Lei, Ing Yann Soon. A multipurpose audio watermarking algorithm with synchronization and encryption[J]. Front. Inform. Technol. Electron. Eng., 2012, 13(1): 11-19.
[14] Zoe Lin Jiang, Jun-bin Fang, Lucas Chi Kwong Hui, Siu Ming Yiu, Kam Pui Chow, Meng-meng Sheng. k-Dimensional hashing scheme for hard disk integrity verification in computer forensics[J]. Front. Inform. Technol. Electron. Eng., 2011, 12(10): 809-818.
[15] Yang Yang, Yu-pu Hu, Le-you Zhang, Chun-hui Sun. CCA2 secure biometric identity based encryption with constant-size ciphertext[J]. Front. Inform. Technol. Electron. Eng., 2011, 12(10): 819-827.