Fast and Efficient Data Masking Method for securing Image over Cloud Computing Environment

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.

A Large Capacity Histogram-Based Watermarking Algorithm for Three Consecutive Bins

The histogram watermark, which performs watermark embedding by slightly modifying the histogram of the original image, has been a hot research topic in information hiding technology due to the superiority of its pixel modification during the watermark embedding process, which is independent of the pixel position. This property makes the histogram-based watermark strong resistant to geometric attacks, such as cropping attack, crossed attack, rotation attack, etc. In this paper, we propose a large capacity histogram-based robust watermarking algorithm based on three consecutive bins for the first time. In our scheme, we divide the shape of three consecutive bins into eight cases. According to these cases, we embed Information Number 0, 1, 2, 3, 4, 5, 6, or 7, respectively. The embedded information capacity reaches one bit per bin (bpb), and the amount of embedded information is equal to 200% of the previous existing algorithms. Experimental results show that the new algorithm not only has a large capacity of embedding information, but also has strong robustness to geometric attacks, as well as common image processing operations.

Scrambling Technology in the Digital Watermarking

In recent years, the digital watermarking technology has been widely used for the copyright protection of the digital images, and a lot of the digital watermarking schemes are proposed. This paper studies the application of shuffling techniques in the digital watermarking and proposes a standard measure of the scrambling degree. The criterion measure can help us judge to what extent an image should be scrambled in order to obtain the best robustness. Finally, this paper puts forward two kinds of scrambling technologies applied in the watermarking system, and the experimental results show that the scrambling technology is very effective in keeping resilience to cropping attack.

Functional Watermarking Algorithm Based on Contourlet Transform and ECC

User-defined functional watermarking algorithm was presented based on contourlet transform field and Ellipse Curve Cryptography（ECC） spatial field. First the edge and direction information of image was obtained by contourlet transform, the discrete functional watermarking was embedded into high frequency parts, and the embedding data was avoided to the image edge. ECC encrypts embedding coordinate’s series. Watermarking changes little original image because of less function data, and attends to zero watermarking algorithms. The results show that the algorithm is invisible to watermarking and also has enough robustness to noise and cropping attack.