LightBlog
Contact at mumbai.academics@gmail.com or 8097636691/9323040215
Responsive Ads Here

Tuesday, 13 February 2018

Designing an Efficient Image Encryption Then Compression System via Prediction Error Clustering and Random Permutation(2014)


Designing an Efficient Image Encryption

 Then Compression System via

 Prediction Error Clustering and Random 

Permutation(2014)


ABSTRACT:
In many practical scenarios, image encryption has to be conducted prior to image compression. This has led to the problem of how to design a pair of image encryption and compression algorithms such that compressing the encrypted images can still be efficiently performed. In this paper, we design a highly efficient image encryption-then-compression (ETC) system, where both lossless and lossy compressions are considered. The proposed image encryption scheme operated in the prediction error domain is shown to be able to provide a reasonably high level of security. We also demonstrate that an arithmetic coding-based approach can be exploited to efficiently compress the encrypted images. More notably, the proposed compression approach applied to encrypted images is only slightly worse, in terms of compression efficiency, than the state-of-the-art lossless/lossy image coders, which take original, unencrypted images as inputs. In contrast, most of the existing ETC solutions induce significant penalty on the compression efficiency.
EXISTING SYSTEM:
 Existing ETC solutions induce significant penalty on the compression efficiency.
DISADVANTAGES OF EXISTING SYSTEM:
Ø More Prediction error.
Ø Lossy Image Compression.
PROPOSED SYSTEM:
Ø In this paper, we design a highly efficient image encryption-then-compression (ETC) system, where both lossless and lossy compression are considered.
Ø The proposed image encryption scheme operated in the predic tion error domain is shown to be able to provide a reasonably high level of security.
Ø We also demonstrate that an arithmetic coding-based approach can be exploited to efficiently compress the encrypted images.
ADVANTAGES OF PROPOSED SYSTEM:
Ø The ability of controlling the lowest achievable rate by the content owner may be treated as an advantageous feature of the proposed ETC scheme, since the quality of the decoded image at receiver side is guaranteed, though the manipulation of the encrypted data is completely handled by an untrusted party.
Ø Attack model applicable to our proposed encryption scheme is the ciphertext-only attack in which the attacker can only access the ciphertext and attempts to recover the original image.
Ø Our proposed compression method on encrypted images is very close to that of the state- of-the-art lossless/lossy image codecs, which receive original, unencrypted images as inputs
MODULES:
 Image Pre-processing Module
 Image Encryption Module
 Image Compression Module
 Image Decryption Module
MODULES DESCRIPTION:
Image Pre-processing Module
ü An image is a two-dimensional picture, which has a similar appearance to some subject usually a physical object or a person. Image is a two-dimensional, such as a photograph, screen display. They may be captured by optical devices—such as cameras, mirrors, lenses, telescopes, microscopes, etc. and natural objects and phenomena, such as the human eye or water surfaces.
ü Compute all the mapped prediction errors.
ü Divide all the prediction errors into clusters.
ü Reshape the prediction errors in each Cinto a 2-D block having four columns.
ü Perform two key-driven cyclical shift operations to each resulting prediction error block, and read out the data in raster-scan order to obtain the permuted cluster.
Image Encryption Module
ü Find the minimum satisfying, and convert into a list of digits with a binary notational system.
ü Solve the discrete optimization problem to find and.
ü In the region defined by, record the coordinate such that,
ü Construct a no repeat random embedding sequence.
ü To encrypt a secret Image bit stream, two pixels in the cover image are selected according to the embedding sequence, and calculate the modulus distance between and, then replace with.
ü Repeat Step 5 until all the secret Image bit streams are encrypted.
Image Compression Module
ü In this section, we discuss the extension of our framework to provide lossy compression of encrypted images.
ü To remedy this problem, quantization on prediction errors needs to be conducted by Alice. In other words, Alice has to be cooperative in order to gain the compression ratios.
Image Decryption Module
ü To extract the encrypted digits, pixel pairs are scanned in the same order as in the encryption procedure. The encrypted secret Image bit streams are the values of extraction function of the scanned pixel pairs.
ü Construct the encrypted sequence.
ü Select two pixels according to the encryption sequence.
ü Calculate, the result is the encryption digit.
ü Repeat Steps 2 and 3 until all the secret Image bit streams are extracted.
ü Finally, the secret Image bits can be obtained by converting the extracted secret Image bit stream.
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
Ø System                          :         Pentium IV 2.4 GHz.
Ø Hard Disk                      :         40 GB.
Ø Floppy Drive                 :         1.44 Mb.
Ø Monitor                         :         15 VGA Colour.
Ø Mouse                            :         Logitech.
Ø Ram                               :         512 Mb.
SOFTWARE REQUIREMENTS:
Ø Operating system           :         Windows XP/7.
Ø Coding Language         :         C#.net
Ø Tool                                  :         Visual Studio 2010

No comments:

Post a Comment