Efficient Data Hiding With LZW Compression and ECC Encryption for Secure Secret Sharing
S.Dhivya Bharathi
#1, K.Saranya
#2, S.Selvakumari, M.Sc., M.Phil,
#3#1UG scholar, #2UG scholar, #3Assistant Professor & Dhanalakshmi Srinivasan College of Arts and Science for Women
Department of Computer Science & Dhanalakshmi Srinivasan College of Arts and Science for Women– Perambalur Tamilnadu, India
1 [email protected], 2 [email protected] Abstract
Information/data hiding is mechanisms which ensure that the occurrence of the secret statistics remains undetected. Two types of data hiding techniques are the majority accepted, they are cryptography and steganography. Where cryptography is knowledge of writing secret code and steganography is art and science of hiding the secret code. In cryptography data is converted to unreadable appearance, so that unauthorized users cannot access the secret data. Steganography system hides message into cover file and create a stegno file. In image steganography there is require of technique which will increase the security, diminish the deformation in the stego file and recovers the data without any loss. In the era of multimedia and internet there is need of dropping time for transmission. The proposed approach is aggregate of compression, facts hiding approach and encryption. To make the transmission and storage of digital data faster, LZW compression technique is used. LZW is a type of lossless compression technique. In the proposed approach Elliptic curve cryptography (ECC) technique is used for data encryption and steganography uses Modified Pixel Value Differencing (MPVD) with LSB method to hide the encrypted data. If the receiver has encryption explanation, then only he can attain the secret communication. These proposed techniques will provide higher security and the system yields high quality image, less memory utilization, more complexity and higher embedded capacity.
Index Terms: Data Hiding, LZW Compression, ECC Encryption, Modified Pixel Value Differencing with LSB Technique, Data and Key Sharing, Data Retrieval.
I. INTRODUCTION
Steganography is the practice of hiding secret messages (hidden text) within every day, seemingly innocuous object (cover text) to produce a stegno text. The beneficiary of a stegno text can use his understanding of the meticulous technique of steganography employed to recuperate the concealed text from the stegno text. The aim of steganography is to allow parties to converse covertly in this sort of way that an attacker cannot tell whether or
not there's hidden that means to their communication. This unit’s steganography apart from cryptography which, even though supplying for private conversation, can arouse suspicion based totally at the fact that it's far getting used.
Steganography sometimes used together with encryption. An encrypted organizer strength still conceal in sequence using steganography, so smooth if the encrypted file is deciphered, the buried information is not seen.
1) Steganography in Image
Digital images are the most broadly used cover file for steganography. Due to the availability of various report formats for diverse packages the set of rules used for these formats differs correspondingly.
Fig 1: Processing steps for Steganography
An image is series of bytes (understand as pixels for images) containing exceptional light intensities in distinctive regions of the image. When coping with virtual images for use with Steganography, 8-bit and 24-bit consistent with pixel picture files are typical. Both have blessings and drawbacks 8-bit images are a best format to apply due to their distinctly small size. The drawback is that only 256 available colorings can be used which can be a potential problem for the duration of encoding. Usually a grey scale colour palette is used whilst coping with eight-bit images such as (.GIF) because its gradual exchange in color could be harder to stumble on after the image has been encoded using the secret message. 24-bit images provide a great deal more flexibility when used for Steganography. The large numbers of colours (over 16 million) that may be used move properly past the human visual device (HVS), which makes it very difficult to discover once a secret message, has been encoded
Great quantity of data can be encoded in to 24-bit images as it is evaluate to 8-bit images. The issue of 24- bit digital images is their size which is very excessive and this makes them suspicious our net due to their heavy size whilst in comparison to eight-bit images. Depending at the form of message and sort of the image distinct algorithms are used.
2) Few types in Steganography in Images:
● Least significant bit insertion
● Masking and filtering
● Redundant Pattern Encoding
● Encrypt and Scatter
● Algorithms and transformations
3) Cryptography
Cryptography is the technological know-how of using arithmetic to encrypt and decrypt data. Cryptography allows storing sensitive records or transmitting it throughout insecure networks (like the Internet) in order that it cannot be examine with the aid of everybody except the intended recipient.
While cryptography is the technology of securing records, crypt analysis is the technology of analyzing and breaking secure conversation. Classical crypt analysis includes an exciting mixture of analytical reasoning, utility of mathematical tool, sample finding, patterns, connection termination and success. Crypt analysts also are known as attackers. Cryptology embraces both cryptography and cryptanalysis.
Cryptography is used in many packages like banking transactions cards, laptop passwords, and e- trade transactions. Three varieties of cryptographic strategies used in fashionable.
1. Symmetric-key cryptography 2. Hash functions.
3. Public-key cryptography
These manuscripts propose a novel algorithm to secrete data inside an image using Steganographic technique. The algorithm that we have proposed is an enhanced version of LSB technique that is not very much robust. Also we've got implemented a compression technique to growth the hiding capacity. This all is demonstrated using an application we have build in Python.
The resulting stego image that we are obtaining after the algorithm completes its execution, is distorted and is easy to detect, that some kind of alteration has been done to the image. So, to enhance the security of the secret message we might be covering the resulting stego image with a new cover image, this is the first level of safety. By just looking at the resulting image nobody would be capable of expect that something is hidden inside it.
In order to growth the encoding potential of the image, a compression algorithm has been used, we realize that each thing of an RGB pixel is represented with 8 bits. So, the most compression would be 8 bits in line with pixel and minimal might be 1 bit per pixel. The proposed Steganographic set of rules incorporates of embedding strategies they are facts hiding method and facts retrieving approach. Data hiding method as the name suggests is used to hide secret message and key within the cover image, whilst data retrieving method is used to retrieve the important thing and the hidden secret message from the stegno image. Therefore data is protected in image without revealing to unauthorized party.
II. RELATED WORKS
Jiantao Zhou, et.al,.[1] Proposed an encrypted-domain RIDH scheme by specifically taking the above- mentioned design preferences into consideration. Since the decoding of the message bits and the unique image is tied together, our proposed technique belongs to the category of non separable RIDH answers. Compared with the latest methods, the proposed approach provides higher embedding capacity and is capable of reap perfect reconstruction of the unique photograph in addition to the embedded message bits. Compare with the inventive unencrypted block, the pixels within the encrypted block have a tendency to have a remote greater uniform distribution. This motivates us to introduce the local entropy into the characteristic vector to capture such one-of-a- kind characteristics
Monika Bartwal, et.al,.[2] In an image by using the redundancy used a key of reversible data embedding for finding an embedding area. To make bigger the other freedom the existing techniques diminish the redundancy by the completing of pixel value computation and make use of image histogram. The modern techniques show unlimited embedding volume without severely demeaning the visual excellence of embedded consequence. The first step is image separation, the inventive uncompressed image is estranged into two fragments A and B; and monitored through the LSBs. A is reversibly entrenched into B, using self-reversible inserting and reversible data hiding technique. LSBs of A can be used to put up extra data. Afterward self embedded data reorganized the encodes image using stream cipher. The values are 0 to 255 and signified by 8 bits. Afterward the encryption process, the data hider put up the encoded image, and insert a limited data into it. The data hider can´t change the original image and only can manage the access to the embedded data. The data mining and data extraction completely differs from image decryption. Two different cases are taking to show.
Ioan Catalin Dragoi, et.al,.[3] RDH scheme for encrypted images based on dividing the encrypted image into blocks and embedding a bit in each block by flipping the 3 least significant bit principles of half the pixels from the obstruct. At the decoding stage, the correlation between the decrypted pixels of each block is used to detect which pixels had their bits flipped. The encrypted images were generated by an exclusive-or operation with pseudo- random bits. The proposed scheme has two distinct versions: a joint method (watermark decoding and image restoration on the decrypted image) and a separate method the encrypted image (generated with) is split by both proposed methods into three distinct sets. Only sets A and B (a total of 2=3 of the image) are used for data hiding,
set U is not modified by the embedding algorithm. That can embed data in at most 1=2 of the image (the other half is used for prediction). The data hiding key is used to determine the order in which the pixels in set A and set B are processed. Set A is the first set to be embedded with the hidden data, the pixels in B are considered as possible hosts only after the capacity offered by A is completely exhausted. The pixels in each set are processed as groups of n pixels and a bit of data will be inserted in each group by modifying their t bit value. After decryption, a user with the hiding key can extract the hidden data by determining the order in which the pixels were embedded and reforming the n pixel groups.
Shuang Yi, et.al,.[4] Propose a new BBE algorithm for reversible data hiding in the encryption domain, which is totally different from traditional RDH methods. BBE can be utilized in different types of images such as binary, gray-scale, medical and cartoon images. Based on BBE, we additional recommend a technique of reversible data hiding in encrypted images, BBE-RDHEI. Compared with accessible state-of-the-art methods, it has significantly enhanced embedding capacity and quality of the discernible decrypted image. BBE-RDHEI can also be simplified and utilized for binary images, while accessible RDHEI methods are calculated only for gray-scale images. To significantly enhance the security level of BBE-RDHEI, we also recommend a security key design mechanism such that BBE-RDHEI is able to resist the differential attack, while existing RDHEI methods cannot. To enhance the robustness of RDHEI methods in withstanding noise and data loss attacks, we introduce a bit-level scrambling process to BBE-RDHEI following secret data embedding to spread out entrenched secret data over the complete marked encrypted image. As a result, BBE-RDHEI is able to recover most of secret data even if one bit- plane of the marked encrypted image is totally removed. Moreover, several bit-level scrambling algorithm can be used in our BBE-RDHEI. This is a supplementary security advantage of BBE-RDHEI.
Xiaochun Cao, et.al,.[5] Proposed HC_SRDHEI method. For the contented owner, the specified cover image is represent according to an over-complete vocabulary by sparse coefficients. Subsequent to that, for the given preferred patches, the consequent coefficients and reconstructed enduring errors are encoded directly without quantization. For most of the patches, the data size is well reduced in the basis of coefficient representation, thus the vacated room is preserved for high capacity data hiding after image encryption. For losslessly recuperating the cover image, the residual errors are self-embedded into the nonselected patches. The learned dictionary is also embedded into the encrypted image for further use. At the receiver side, when the receivers accept an encrypted image containing additional data, the processing procedure depends on the role of receiver. If the receiver is a data hider and only has the data hiding key, he can extract the data without knowing the image content. If the receiver is an image owner and only has the encryption key, he can decrypt the image with a better quality. If the receiver is both the image owner and data hider, he has both of two keys in such case. Thus, the data extraction and content recovery are all done, and both results are free of error. In synopsis, for our planned framework, the data extraction and image recovery are distinguishable and reversible.
III. EXISTING METHODOLOGIES
The RDH-EI permit a server to implant additional message into an encrypted image uploaded by the contented owner, and guarantees that the innovative content can be loss lessly recovered after decryption on the recipient side.
Commonly, reversibility is strongly associated to the embedding consignment. If the original image can be lossless recovered when the payload does not exceed the achievable capacity, we say it is reversible. Meanwhile, RDH-EI protocols are continually designed for natural images. Since a natural image continually incorporates big smooth regions, i.e., redundancies, you possibly can embed records into the original image and loss lessly recovers it. In existing steganography approach, image has become an essential, potential, and popular file to be used as the carrier file for protecting the confidential information. But essentially, the theory had said that every of the digital files could be worn as a carrier categorizer or the message. The existing method involves aggregate of Arithmetic Coding to offer excessive embedding capacity, encryption through AES, and Modified embedding scheme which includes pixel optimization.
1) AES Encryption
The AES cipher is also progression to as the block cipher. It has achievement attack has been mentioned on AES.
Some advantages of AES are easy to enforce on 8-bit structure processors and powerful implementation on 32-bit architecture processors. AES encryption is accomplished in more than one round. Each round has 4 important steps along with sub-byte, shift row, mix column and add round key. Sub-byte is the substitution of bytes using look-up table. Shift row is the transferring of rows according to byte length. Mix column is multiplication over Galois field matrix. Finally, within the upload spherical key step, the output matrix of mix column is XORed with the round key.
The wide variety of rounds used for encryption relies upon on the important thing size. For a 128-bit key, these 4 steps are implemented to nine rounds, in which the 10th round does no longer consider the mixture column step.
Since all steps are recursive, decryption is the opposite of encryption.
2) Algorithm Procedure
The set of rules starts with an Add round key degree observed by using 9 rounds of 4 levels and a tenth round of three stages. This applies for both encryption and decryption with the exception that every degree of round the decryption set of rules is the inverse of its counterpart within the encryption algorithm. The four degrees are as follows:
1. Substitute bytes 2. Shift rows 3. Mix Columns 4. Add Round Key
The 10th round definitely leaves out the Mix Columns stage. The first 9 rounds of the decryption algorithm consist of the subsequent:
1. Inverse Shift rows 2. Inverse Substitute bytes 3. Inverse Add Round Key 4. Inverse Mix Columns
Again, the 10th round simply leaves out the Inverse Mix Columns level. Each of these stages will now be considered in greater element.
IV. SECURE DATA ACCESS WITH AES ENCRYPTION AND TIMEBASED KEY SHARING
In steganography, image has become a necessary, potential, and admired categorizer to be used as the carrier file for defensive the confidential in sequence. But really, the supposition had said that every of the digital files could be used as a carrier file or the message. The secret message, envelop message, embedding algorithm and the secret key are the major four terminologies used in the steganography systems. The secret message is defined as the statistics or information which is needed to be unknown in the suitable digital media. The envelop message is measured as the carrier of the concealed message such as image, video, text or any other digital media. The embedding algorithm is the most significant part; it can be defined as a technique or the thoughts that frequently used to embed the secret in sequence in the cover message to prevent unauthorized people to get it. The MPVD with LSB coding is suitable to work with any type of data file format, hence effortlessly combine with any procedure, but unfortunately, MPVD with LSB encoding lack robustness and security. In this practice the data are only hidden in the last bit, which subordinate its importance.
The proposed approach is combination of compression, facts hiding technique and encryption. To construct the transmission and storage of digital statistics faster, HLZW compression practice is used. HLZW is a category of lossless compression technique. In the proposed approach AES (Advanced Encryption Standard) technique is used for data encryption and also Comprehensive Steganographic method by combining the lossless compression, state of the art encryption, modified pixel value differencing (MPVD) and LSB substitution. If the receiver has encryption key, then only he can attain the surreptitious message. These proposed techniques will provide higher security and the system yields high quality image, less memory utilization, more complexity and higher embedded capacity.
V. METHODOLOGY FOR THE PROPOSED WORK 1) Elliptical Curve Cryptography (ECC)
Elliptic Curve Cryptography (ECC) is a way to public-key cryptography set up on the algebraic constitution of elliptic curves over finite fields. ECC requires smaller keys compared to non-ECC cryptography (centered on
undeniable Galois fields) to provide similar security. Elliptic curves are applicable for key contract, digital signatures, pseudo-random generators and different duties. Indirectly, they may be able to be used for encryption by using combining the important thing agreement with a symmetric encryption scheme. They are also used in a couple of integer factorization algorithms based on elliptic curves that have purposes in cryptography, similar to Lenstra elliptic-curve factorization.
Elliptical curve cryptography (ECC) is a type of public key encryption approach. In Elliptic curve perceptions that can be create fast, smaller, and more effective cryptographic keys. ECC generates keys by means of the houses of the elliptic curve equation instead of the typical approach of new release because the product of very tremendous prime numbers. The technological know-how can be utilized together with most public key encryption ways, comparable to RSA, and Diffie-Hellman. In accordance to some researchers, ECC can yield a stage of safety with a 164-bit key that different systems require a 1,024-bit key to achieve. Seeing that ECC helps to establish similar protection with lessen computing power and battery resource usage, it is becoming greatly used for cellular purposes. ECC was once residential throughout Certicom, a mobile e-business fortification supplier, and was once not too long ago licensed by means of Hifn, a brand of built-in circuitry (IC) and network security merchandise.
RSA has been surroundings up it are possessing variation of ECC.
Public-key cryptography is based on the intractability of distinctive mathematical issues. Early public-key methods are cozy assuming that it is tricky to element a massive integer composed of two or extra giant top causes. The security of elliptic curve cryptography is dependent upon the capability to compute a aspect multiplication and the lack of ability to compute the multiplicand given the customary and product points. The size of the elliptic curve determines the problem of the concern. The primary improvement promised through elliptic curve cryptography is a smaller key dimension, lowering storage and transmission requisites.
2) STEPS IN ECC ALGORITHM
Encryption
• Define a Curve.
• Produce public private Key pair exploit of that curve, for every sender and receiver.
• Create a shared secret key from the key pair.
• From that shared secret key, create an encryption key.
• Using that encryption key and asymmetric encryption set of rules, encrypt the facts to send.
Decryption
The sender will both share the curve with receiver or sender and receiver will have the equal use for the equal curve form. Also, sender will send its public key to the receiver.
1. Generate public personal Key pair using the same curve for that curve for receiver.
2. Regenerate a shared secret key utilizing private key of receiver and public key of sender.
3. From that shared secret key, create an encryption key.
4. Utilizing that encryption key and symmetric encryption algorithm, decrypt the information.
VI. PROCEDURE
● Create Secret Message and Cover file
● LZW Compression
● Data Encryption
● Data Hiding using LSB
● Data Extraction
a. Create Secret Message and Cover file
Data hiding is the development of hiding secret communication into cover file. In steganography, before the hiding process, the sender must select an appropriate message carrier, an effective message to be hidden as well as a secret key used as a password. Secret message is there in the appearance of text and cover file is preferred in outline of image. A robust Steganographic set of rules need to be decided on that must be capable of encrypt the message extra correctly. The sender then may additionally send the hidden message to the receiver by way of the usage of any of the current conversation techniques. Uploaded text message was hidden within the image to create stegno image.
Generate key for securely sharing the information to receiver.
b. LZW Compression
Secret message is assemble from sender and apply compression on secret text to diminish the dimension of the compressed text. LZW compression is the process of reducing the size of textual content before hiding in image.
LZW compression is the compression of a document into a smaller file the usage of a table-based lookup set of rules. LZW compression set of rules takes each input sequence of bits of a given duration for that specific bit sample, such as the sample itself and a shorter code.
c. Data Encryption
During encryption progression the plaintext is converting into cipher text. Here compressed text is taken as input for encryption development. ECC encryption is used to exchange the compressed text into encrypted format.
Then secret keys are generate and disseminated to the receiver. Compressed manuscript is taken as contribution for encryption using ECC. It creates encryption keys based on using points on a curve to describe the public and private keys. It provides more protected data sharing with lesser key size compared to other Cryptographic techniques.
Encrypted output is transformed into binary form. It ensures higher security level.
d. Data Hiding using LSB
In the progression of embedding, the cover image is separated into non-overlapping pixel blocks of 3x3 or 2x2 pixel blocks. Block levels are based cardinality of the envelop image. If secret bit is 1 and LSB of stego pixel is 0 or vice-versa, then 1 is added or subtract to the stego pixel. In this technique, the LSB of every pixel is replace (over-written) by a value zero for the non-edged pixel, or one for an edged pixel. This can be complete by using the logical operator. The Least Significant Bit contains the indication for the existence of edged pixel. Changes to the LSB of a pixel concern its price by only one. Since pixel values range from 0 to 255, there will be an extremely modest change in pixel intensity. The extraction of the LSB can be implemented by checking the odd and even pixel values.
e. Data Extraction
Data extraction is the procedure of extracting the original data. Receiver gets the secret message with cover image.
Specific key is generate and shared to the receiver during the progression of message sending. Key sharing is the process of allocation secret keys to the receiver. Then the receiver preserve remove the text and decrypt the text using decryption key. Then insert decompression to get innovative text.
Fig 2: Architecture for Proposed Work
VII. CONCLUSION
This paper proposed a new Steganographic set of rules for hiding textual content files in images. Here provide a top level view of steganography and introduce a few strategies of steganography which help to embed the facts. These strategies are extra useful for detecting the stegno images in addition to the picture media relating to protection of images and embed the facts for complicated image place and can effortlessly estimate the high embedding capacity by way of using the quantitative steganalytic method. Here we've also used an underlying compression algorithm
with maximum compression ratio of eight bits/ pixel. Developed a machine in .net primarily based at the proposed set of rules. Here we've examined few images with one-of-a-kind sizes of textual content documents to be hidden and concluded that the resulting stego images do not have any great changes. Also we discovered that for .Bmp images this set of rules works very effectively. Hence this new Steganographic method is powerful and very efficient for hiding text files in images.
VIII. REFERENCE
[1] Zhou, Jiantao, Weiwei Sun, Li Dong, Xianming Liu, Oscar C. Au, and Yuan Yan Tang. "Secure reversible image data hiding over encrypted domain via key modulation." IEEE transactions on circuits and systems for video technology 26, no. 3 (2016): 441-452.
[2] Zhang, Xinpeng, Jing Long, Zichi Wang, and Hang Cheng. "Lossless and reversible data hiding in encrypted images with public-key cryptography." IEEE Transactions on Circuits and Systems for Video Technology 26, no. 9 (2016): 1622-1631.
[3] Dragoi, Ioan Catalin, Henri-George Coanda, and Dinu Coltuc. "Improved reversible data hiding in encrypted images based on reserving room after encryption and pixel prediction." In 2017 25th European Signal Processing Conference (EUSIPCO), pp. 2186-2190. IEEE, 2017.
[4] Yi, Shuang, and Yicong Zhou. "Binary-block embedding for reversible data hiding in encrypted images." Signal Processing133 (2017): 40-51.
[5] Cao, Xiaochun, Ling Du, Xingxing Wei, Dan Meng, and Xiaojie Guo. "High capacity reversible data hiding in encrypted images by patch-level sparse representation." IEEE transactions on cybernetics 46, no. 5 (2016): 1132- 1143.
[6] Chuman, Tatsuya, Kenta Kurihara, and Hitoshi Kiya. "On the security of block scrambling-based etc systems against extended jigsaw puzzle solver attacks." IEICE TRANSACTIONS on Information and Systems 101, no. 1 (2018): 37-44.
[7] Kurihara, Kenta, Masanori Kikuchi, Shoko Imaizumi, Sayaka Shiota, and Hitoshi Kiya. "An encryption-then- compression system for jpeg/motion jpeg standard." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences 98, no. 11 (2015): 2238-2245.
[8] Chuman, Tatsuya, Kenta Iida, and Hitoshi Kiya. "Image manipulation on social media for encryption-then- compression systems." In 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), pp. 858-863. IEEE, 2017.
[9] Kobayashi, Hiroyuki, and Hitoshi Kiya. "Bitstream-Based JPEG Image Encryption with File-Size Preserving."
In 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE), pp. 384-387. IEEE, 2018.
[10] Qian, Zhenxing, Hang Zhou, Xinpeng Zhang, and Weiming Zhang. "Separable reversible data hiding in encrypted JPEG bitstreams." IEEE Transactions on Dependable and Secure Computing (2016).