计算机应用 ›› 2013, Vol. 33 ›› Issue (09): 2497-2500.DOI: 10.11772/j.issn.1001-9081.2013.09.2497

• 信息安全 • 上一篇    下一篇

云模型图像置乱算法

范铁生1,张忠清1,孙静1,罗雪春2,陆贵强3,张璞1   

  1. 1. 辽宁大学 信息学院,沈阳 110036;
    2. 辽宁大学 文科综合实验中心,沈阳 110036;
    3. 辽宁广播电视大学 信息化建设中心,沈阳 110034
  • 收稿日期:2013-03-20 修回日期:2013-04-23 出版日期:2013-09-01 发布日期:2013-10-18
  • 通讯作者: 范铁生
  • 作者简介:范铁生(1955-),男,辽宁沈阳人,教授,主要研究方向:信息隐藏、声纹识别、图像处理;
    张忠清(1984-),女,山东济宁人,硕士,主要研究方向:图像处理、数字水印、虚拟现实;
    孙静(1979-),女,辽宁抚顺人,博士,主要研究方向:金融工程;
    罗雪春(1965-),男,辽宁盖州人,高级工程师,主要研究方向:软件测试环境、粒子群优化;
    陆贵强(1970-),男,辽宁朝阳人,硕士,主要研究方向:远程教育、Web信息处理;
    张璞(1987-),男,陕西西安人,硕士,主要研究方向:虚拟现实、云计算、分布式计算。

Image scrambling algorithm based on cloud model

FAN Tiesheng1,ZHANG Zhongqing1,SUN Jing1,LUO Xuechun2,LU Guiqiang3,ZHANG Pu1   

  1. 1. Information Institute, Liaoning University, Shenyang Liaoning 110036, China;
    2. Comprehensive Experiment Center of Arts, Liaoning University, Shenyang Liaoning 110036, China;
    3. Informatization Construction Center, Liaoning Radio and TV University, Shenyang Liaoning 110034, China
  • Received:2013-03-20 Revised:2013-04-23 Online:2013-10-18 Published:2013-09-01
  • Contact: FAN Tiesheng

摘要: 针对目前数字图像置乱算法在双重置乱方面的欠缺问题,提出一种新的云模型图像置乱算法。该算法利用三维云模型生成的函数值来改变图像像素位置和像素值,实现了双重置乱。经实验验证以及定量定性分析,置乱图像呈现白噪声,真正实现了图像置乱,并不存在周期性恢复的安全问题,该算法能较快达到理想的置乱效果,且能抵抗一定的剪切、加噪、滤波以及缩放攻击;证明了该算法的有效性和合理性,可以较好地应用于图像置乱。

关键词: 图像置乱, 云模型, 双重置乱, 置乱程度

Abstract: Concerning the deficiency of the digital image scrambling algorithm in double scrambling, an image scrambling algorithm based on cloud model was proposed. The algorithm used the function value generated by the three-dimensional cloud model to change the positions and values of the image pixels, to achieve a double scrambling. The experimental verification as well as quantitative and qualitative analysis show that the scrambling image renders white noise and realizes the image scrambling. There is no security issue on cyclical recovery. The algorithm can quickly achieve the desired effect, resistant to shear, plus noise, filtering and scaling attacks. This proves that the algorithm is effective and reasonable, and also can be better applied to the image scrambling.

Key words: image scrambling, cloud model, double scrambling, scrambling degree

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