The Kolmogorov Spline Network for Authentication Data Embedding in Images

2013 ◽  
pp. 96-114
Author(s):  
Pierre-Emmanuel Leni ◽  
Yohan D. Fougerolle ◽  
Frédéric Truchetet
Keyword(s):  
Continuous Functions ◽  
Data Embedding ◽  
Progressive Transmission ◽  
Secret Key ◽  
Transmission Scheme ◽  
Black And White ◽  
Novel Approach ◽  
Univariate Functions ◽  
Univariate Representation ◽  
Superposition Theorem

In 1900, Hilbert declared that high order polynomial equations could not be solved by sums and compositions of continuous functions of less than three variables. This statement was proven wrong by the superposition theorem, demonstrated by Arnol’d and Kolmogorov in 1957, which allows for writing all multivariate functions as sums and compositions of univariate functions. Amongst recent computable forms of the theorem, Igelnik and Parikh’s approach, known as the Kolmogorov Spline Network (KSN), offers several alternatives for the univariate functions as well as their construction. A novel approach is presented for the embedding of authentication data (black and white logo, translucent or opaque image) in images. This approach offers similar functionalities than watermarking approaches, but relies on a totally different theory: the mark is not embedded in the 2D image space, but it is rather applied to an equivalent univariate representation of the transformed image. Using the progressive transmission scheme previously proposed (Leni, 2011), the pixels are re-arranged without any neighborhood consideration. Taking advantage of this naturally encrypted representation, it is proposed to embed the watermark in these univariate functions. The watermarked image can be accessed at any intermediate resolution, and fully recovered (by removing the embedded mark) without loss using a secret key. Moreover, the key can be different for every resolution, and both the watermark and the image can be globally restored in case of data losses during the transmission. These contributions lie in proposing a robust embedding of authentication data (represented by a watermark) into an image using the 1D space of univariate functions based on the Kolmogorov superposition theorem. Lastly, using a key, the watermark can be removed to restore the original image.

scholarly journals DWT Based Image Steganography with Seven Segment Display Pattern as a Key

2019 ◽  
Vol 8 (10S) ◽  
pp. 164-169 ◽  
Keyword(s):  
Field Programmable Gate Array ◽  
Image Steganography ◽  
Data Embedding ◽  
Secret Key ◽  
Novel Approach ◽  
Field Programmable ◽  
Speed Up ◽  
Gate Array ◽  
Reconfigurable Device

Steganography is one of the commanding and commonly used methods for embedding data. Realizing steganography in hardware supports to speed up steganography. This work realizesthe novel approach for generation of Key, for hiding and encoding processes of image steganography using LSB and HAAR DWT.The data embedding process is realized with seven segment display pattern as a secret key with various sizes using HAAR DWT and LSB. Maximum hiding effectiveness is also attained from this work. The same is implemented in hardware using reconfigurable device Field programmable gate array to improve the speed, area and power. The proposed work is also evaluated improved PSNR using MATLAB.

The Kolmogorov Spline Network for Image Processing

2013 ◽  
pp. 54-78
Author(s):  
Pierre-Emmanuel Leni ◽  
Yohan D. Fougerolle ◽  
Frédéric Truchetet
Keyword(s):  
Image Processing ◽  
Progressive Transmission ◽  
Original Image ◽  
Jpeg 2000 ◽  
Compression Scheme ◽  
Construction Methods ◽  
Reconstruction Quality ◽  
Univariate Function ◽  
Univariate Functions ◽  
Image Pixels

In 1900, Hilbert stated that high order equations cannot be solved by sums and compositions of bivariate functions. In 1957, Kolmogorov proved this hypothesis wrong and presented his superposition theorem (KST) that allowed for writing every multivariate functions as sums and compositions of univariate functions. Sprecher has proposed in (Sprecher, 1996) and (Sprecher, 1997) an algorithm for exact univariate function reconstruction. Sprecher explicitly describes construction methods for univariate functions and introduces fundamental notions for the theorem comprehension (such as tilage). Köppen has presented applications of this algorithm to image processing in (Köppen, 2002) and (Köppen & Yoshida, 2005). The lack of flexibility of this scheme has been pointed out and another solution which approximates the univariate functions has been considered. More specifically, it has led us to consider Igelnik and Parikh’s approach, known as the KSN which offers several perspectives of modification of the univariate functions as well as their construction. This chapter will focus on the presentation of Igelnik and Parikh’s Kolmogorov Spline Network (KSN) for image processing and detail two applications: image compression and progressive transmission. Precisely, the developments presented in this chapter include: (1)Compression: the authors study the reconstruction quality using univariate functions containing only a fraction of the original image pixels. To improve the reconstruction quality, they apply this decomposition on images of details obtained by wavelet decomposition. The authors combine this approach into the JPEG 2000 encoder, and show that the obtained results improve JPEG 2000 compression scheme, even at low bitrates. (2)Progressive Transmission: the authors propose to modify the generation of the KSN. The image is decomposed into univariate functions that can be transmitted one after the other to add new data to the previously transmitted functions, which allows to progressively and exactly reconstruct the original image. They evaluate the transmission robustness and provide the results of the simulation of a transmission over packet-loss channels.

A Novel Approach Using Steganography and Cryptography in Business Intelligence

2021 ◽  
pp. 192-217
Author(s):  
Sabyasachi Pramanik ◽  
Ramkrishna Ghosh ◽  
Mangesh M. Ghonge ◽  
Vipul Narayan ◽  
Mudita Sinha ◽  
...  
Keyword(s):  
Data Mining ◽  
Image Encryption ◽  
Encryption Scheme ◽  
Secret Key ◽  
Cryptographic Algorithm ◽  
Novel Approach ◽  
Optimal Accuracy ◽  
Direct Data ◽  
Lsb Technique ◽  
Encryption Method

In the information technology community, communication is a vital issue. And image transfer creates a major role in the communication of data through various insecure channels. Security concerns may forestall the direct sharing of information and how these different gatherings cooperatively direct data mining without penetrating information security presents a challenge. Cryptography includes changing over a message text into an unintelligible figure and steganography inserts message into a spread media and shroud its reality. Both these plans are successfully actualized in images. To facilitate a safer transfer of image, many cryptosystems have been proposed for the image encryption scheme. This chapter proposes an innovative image encryption method that is quicker than the current researches. The secret key is encrypted using an asymmetric cryptographic algorithm and it is embedded in the ciphered image using the LSB technique. Statistical analysis of the proposed approach shows that the researcher's approach is faster and has optimal accuracy.

scholarly journals Code-Hopping Based Transmission Scheme for Wireless Physical-Layer Security

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Liuguo Yin ◽  
Wentao Hao
Keyword(s):  
Communication Systems ◽  
Data Encryption ◽  
Physical Layer ◽  
Parity Check ◽  
Secret Key ◽  
Application Layer ◽  
Transmission Scheme ◽  
Check Matrix ◽  
Secret Keys ◽  
Source Message

Due to the broadcast and time-varying natures of wireless channels, traditional communication systems that provide data encryption at the application layer suffer many challenges such as error diffusion. In this paper, we propose a code-hopping based secrecy transmission scheme that uses dynamic nonsystematic low-density parity-check (LDPC) codes and automatic repeat-request (ARQ) mechanism to jointly encode and encrypt source messages at the physical layer. In this scheme, secret keys at the transmitter and the legitimate receiver are generated dynamically upon the source messages that have been transmitted successfully. During the transmission, each source message is jointly encoded and encrypted by a parity-check matrix, which is dynamically selected from a set of LDPC matrices based on the shared dynamic secret key. As for the eavesdropper (Eve), the uncorrectable decoding errors prevent her from generating the same secret key as the legitimate parties. Thus she cannot select the correct LDPC matrix to recover the source message. We demonstrate that our scheme can be compatible with traditional cryptosystems and enhance the security without sacrificing the error-correction performance. Numerical results show that the bit error rate (BER) of Eve approaches 0.5 as the number of transmitted source messages increases and the security gap of the system is small.

scholarly journals A Three-Stage Progressive Transmission Scheme for Virtual Environments Over Lossy Networks

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 184411-184422
Author(s):  
Yitong Liu ◽  
Jingfeng Guo ◽  
Ken Deng ◽  
Yishi Liu
Keyword(s):  
Virtual Environments ◽  
Progressive Transmission ◽  
Transmission Scheme ◽  
Lossy Networks

scholarly journals Generation of Keystream for Symmetric Cipher using U-Matrix

2019 ◽  
Vol 8 (3) ◽  
pp. 3679-3685
Keyword(s):  
Key Management ◽  
Experimental Results ◽  
Public Key ◽  
Secret Key ◽  
Main Challenge ◽  
Novel Approach ◽  
Symmetric Key ◽  
Symmetric Key Cryptography

Symmetric-key cryptography is a classical cryptography in which both sender and receiver use the same key K to encrypt and decrypt the message. The main challenge between sender and receiver is to agree upon the secret-key which should not be revealed to public. Key management is the major issue in symmetric-key cryptosystem. To avoid these, a novel approach in generating the keystream Ks for any symmetric-key algorithms using U-matrix is proposed in this paper. The advantage of this method is generation of key K from Ks is based on some deterministic procedure which is then applied to DES algorithm and K is not necessarily remembered by both sender and receiver. Further, in each round different key is used as opposed to usage of single key in classical DES. Experimental results clearly show the security is increased when it is compared with classical DES.

scholarly journals Multilayer neural network synchronized secured session key based encryption in wireless communication

2019 ◽  
Vol 14 (1) ◽  
pp. 169 ◽  
Author(s):  
Arindam Sarkar ◽  
Joydeep Dey ◽  
Anirban Bhowmik
Keyword(s):  
Neural Network ◽  
Wireless Communication ◽  
Frequency Analysis ◽  
Multilayer Perceptron ◽  
Secret Key ◽  
Session Key ◽  
Novel Approach ◽  
Layered Networks ◽  
Hidden Layer ◽  
Energy Computation

<p>Energy computation concept of multilayer neural network synchronized on derived transmission key based encryption system has been proposed for wireless transactions. Multilayer perceptron transmitting machines accepted same input array, which in turn generate a resultant bit and the networks were trained accordingly to form a protected variable length secret-key. For each session, different hidden layer of multilayer neural network is selected randomly and weights of hidden units of this selected hidden layer help to form a secret session key. A novel approach to generate a transmission key has been explained in this proposed methodology. The last thirty two bits of the session key were taken into consideration to construct the transmission key. Inverse operations were carried out by the destination perceptron to decipher the data. Floating frequency analysis of the proposed encrypted stream of bits has yielded better degree of security results. Energy computation of the processed nodes inside multi layered networks can be done using this proposed frame of work.</p>

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