Combination of Hiding and Encryption for Data Security

—One of the techniques used in information security is the concealment technique, where the information to be hidden within another information medium to be saved in the process of messaging between two sides without detection. In this paper, an algorithm was proposed to conceal and encrypt data using several means.in order to ensure its preservation from detection and hackers. Wavelet transformer was used to change the shape of a wave of information (one and two-dimensional data) and its different mathematical formulas. Two sets of data were used, the first group used in a hidden process. The second group was considered as a means of both embedding and encryption. The data in the second group is reduced to the extent of sufficient for the modulation process, by extracting its high-value properties and then removing them from the mother's information wave. The process of encrypting of the two sets of data comes together using an exponential function. The result is undetectable information signals. Algorithms were built to hide and encrypt one and two-dimensional data. High-security signals and images were obtained. Decryption algorithms were built to return encrypted data to their original forms, and getting the replica data.


Introduction
Cryptography and steganography are common methods to secure communications. For the purpose of protection against unauthorized access, confidentiality and data integrity must be observed. Cryptography scrambles a message so it cannot be understood. The Steganography hides the message so it cannot be seen [1,2]. This research is made to combine both cryptography and Steganography methods into one system for better confidentiality and security. In this advanced encrypting data hiding method, encrypted data can be embedded and extracted from both encrypted images

Wavelet transformer
Wavelet conversion is known to convert other data types from time domain to frequency domain. It is used to analyze a signal that does not produce information about "frequency" in the traditional sense, but a time and size distribution is created. The change in the size of the wavelet is represented by a two factor. It is therefore possible to reconstruct any signal using one wave as a base and to place as many waves as needed at different times with different amplitudes and scales [12][13][14].The equations for conversion can be summarized as follows: Where: x is chosen data. g is high pass filter. h is low pass filter. This decomposition reduced the time resolution by half as half of each output filter distinguishes the signal. However, each output has half the frequency band of the input, thus multiplying the frequency resolution [15,16].
using a DNA and Amino Acids-Based Play fair cipher. While in the second phase the encrypted data is steganography ally hidden into some reference DNA sequence using an insertion technique. In [19]proposed an LSB & DCT-based steganography method for hiding the data. Each bit of data is embedded by altering the least significant bit of low frequency DCT coefficients of cover image blocks. They used some techniques to utilizes the idea of SSB-4 technique in modifying the other bits to obtain the minimum variation between the original and the modified coefficient. The author in [20] explored the limits of Steganography theory and practice. He printed out the enhancement of the image Steganography system using LSB approach to provide a means of secure communication. A stego-key has been applied to the system during embedment of the message into the cover image. The recent explosion of research in watermarking to protect intellectual property is evidence that Steganography is not just limited to military or espionage applications.In [21]designed sequence the combined scrambling operation is utilized for changing the pixel position of secret image under the control of a random matrix. At the same time, the pixel value is altered by random bit shift for obtaining an encrypted image encoded in N-bit data. These operations are employed for all pixels of original secret image. The authors in [22], they proposed a method, which combines the techniques of Steganography and cryptography, to hide the secret data in an image. In the first phase, the sender will embed the secret data in an image by using the Least Significant Bit (LSB) technique. The embedded image will be encrypted by using an encryption algorithm. In [23], they Advanced Encryption Standard (AES) algorithm has been modified and used to encrypt the secret message. the encrypted message has been hidden by Enhancing Pixel Value Difference (PVD) image using Mobile Phone Keypad (MPK) Coding. In [24], they introduced PASH, a privacy-aware s-health access control system, which the key ingredient is a large universe CP-ABE with access policies partially hidden. In PASH, attribute values of access policies are hidden in encrypted SHRs and only attribute names are revealed.

Quality Measures of the Method
In order to assess the quality of the method of hiding and encrypting information, commonly used measures are, arithmetic mean (average), and entropy. Mean is used to quantify the difference between the initial (cover signal) or (modulated signal) and the Mixed encrypted hidden signal, distorted signal, equation (3) [25][26]. Entropy is the average rate at which information is produced by a stochastic source of data. The measure of information entropy associated with each possible data value is the negative logarithm of the probability mass function for the value equation (4) [27][28][29].
Where: ai = elements. n = number of elements.
Where: I1(i,j) = the value of pixel at (i,j) of the original image. ̅ 1 = the mean of the original image.
I2(i,j) = the value of pixel at (i,j) of reconstructed image. ̅ 2 = the mean of the reconstructed image.
(i,j) = row and column numbers.

Algorithms and Results
In this section of this research, the algorithms designed to build the proposed work will be presented with the results obtained. Calculations were performed and all algorithm were implemented using MATLAB. Each cryptographic algorithm will be presented for each case discussed with decipher algorithm as well as the results for both cases, as follows: Table 1. ALGORITHM (1-a): encryption of one-dimension signal for two cases, low frequency signal (LFS) sine wave and high frequency (HFS) of EEG signal.

ALGORITHM (1-a): Encryption Algorithm
Read the first data signal with high frequency, modulated signal, signal=m sample. Read second data signal with low frequency signal (LFS) or high frequency signal (HFS) to be encrypted and hidden, EEG or sin=n sample. Decompose the first signal (modulated signal) using wavelet packet transform law (wpt): wpt=wpdec(signal, 3, 'db1'). Find the best tree of (wpt) using the rule: bt=besttree(wpt). Find the coefficients of (besttree). Link these coefficients together to get the modulated signal (the mother signal=m samples). Zeroing the positive values of the mother signal after saving them and their locations, c11, loc1. Decompose second signal (signal to hide) using the second wavelet transform law: [C, L]=wavedec(sin, 3, 'db1'), C=n samples.

2.
Read second image with lower dimensions; image to be encrypted and hidden, tree image (258x350).

4.
Zeroing the positive values of the mother image, (modulated signal=c1) after saving them and their locations, c11, loc1.

5.
Zeroing the negative values of image to hide, (signal to hide=c2) after saving them and their locations, c12, loc2.

6.
Make modulation process, as follow:   Table (1) illustrates the quality measurements used for the purpose of showing the efficiency of the method and comparing cases before and after the hiding and encryption operations. The measurements entropy and average were used, as follows:

Conclusion
Many important things can be concluded during of experiments results, it is noticed from (Table 1), the average of encrypted signal differs from both of signals before encryption because of embedding signals' process. And the entropy of encrypted signal is less than of the two signals before encryption, which means the characteristics which distinguished each signal are completely lost after they are combined into a single signal. Using of the exponential function as an intermediary in the encryption process has proven successful by obtaining completely different results from the original. The whole encryption process gave us forms of information has no similarity to the original. After removing the cover and decrypting, the resulting image or signal is exactly identical to the original.