Fast and Efficient Data Masking Method for Securing Image Over Cloud Computing Environment

Abstract

Objective: Preserving confidentiality of sensitive information is becoming more and more difficult and challenging considering current scenarios as huge amount of multimedia data are stored and communicated over internet among users and cloud computing environment. The existing cryptography security model for storing image on cloud platform cannot resist against various kind of modern attack such as statistical, differential, brute force, cropping attack etc. an improved bit scrambling technique using chaotic maps that can resist against various kind of security attack. The FEDM cipher image provides less correlation among neighboring pixels and image can be decrypted even under presence of noise. To achieve better UACI, NPCR, histogram, runtime, and processing time performance than existing image security methods. Methods: Preserving con fidentiality of sensitive information is becoming more and more difficult and challenging considering current scenarios as huge amount of multimedia data are stored and communicated over internet among users and cloud computing environment. The existing cryptography security model for storing image on cloud platform cannot resist against various kind of modern attack such as statistical, differential, brute force, cropping attack etc. Results: From overall result attained shows, the proposed FEDM model attain much superior performance considering histogram, UACI, NPCR, and runtime. The FEDM model can resist against SA. The FEDM model attain better performance because IBS is used in each step of CS. Thus, correlation among adjacent pixel is less and aiding superior security performance. Further, the FEDM model attain better UACI and NPCR performance when compared with exiting image encryption model.