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A Proposed Algorithm for Encrypted Data Hiding in Video Stream Based on Frame Random Distribution
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     The science of information security has become a concern of many researchers, whose efforts are trying to come up with solutions and technologies that ensure the transfer of information in a more secure manner through the network, especially the Internet, without any penetration of that information, given the risk of digital data being sent between the two parties through an insecure channel. This paper includes two data protection techniques. The first technique is cryptography by using Menezes Vanstone elliptic curve ciphering system, which depends on public key technologies. Then, the encoded data is randomly included in the frame, depending on the seed used. The experimental results, using a PSNR within average of 65 and MSE within average of 85, indicate that the proposed method has proven successful in its ability to efficiently embedding data.

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
An Efficient Shrinkage Estimators For Generalized Inverse Rayleigh Distribution Based On Bounded And Series Stress-Strength Models
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Abstract<p>In this paper, we investigate two stress-strength models (Bounded and Series) in systems reliability based on Generalized Inverse Rayleigh distribution. To obtain some estimates of shrinkage estimators, Bayesian methods under informative and non-informative assumptions are used. For comparison of the presented methods, Monte Carlo simulations based on the Mean squared Error criteria are applied.</p>
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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Approach for estimating the unknown Scale parameter of Erlang Distribution Based on General Entropy Loss Function
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We are used Bayes estimators for unknown scale parameter  when shape Parameter  is known of Erlang distribution. Assuming different informative priors for unknown scale  parameter. We derived The posterior density with posterior mean and posterior variance using different informative priors for unknown scale parameter  which are the inverse exponential distribution, the inverse chi-square distribution, the inverse Gamma distribution, and the standard Levy distribution as prior. And we derived Bayes estimators based on the general entropy loss function (GELF) is used the Simulation method to obtain the results. we generated different cases for the parameters of the Erlang model, for different sample sizes. The estimates have been comp

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Publication Date
Wed Jan 12 2022
Journal Name
Iraqi Journal Of Science
Constructing of Analysis Mathematical Model for Stream Cipher Cryptosystems
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The aim of this paper is to construct the analysis mathematical model for stream cipher cryptosystems in order to be cryptanalysis using the cryptanalysis tools based on plaintext attack (or part from it) or ciphertext only attack, choosing Brüer generator as study case of nonlinear stream cipher system.
The constructing process includes constructing the linear (or non-linear) equations system of the attacked nonlinear generator. The attacking of stream cipher cryptosystem means solving the equations system and that means finding the initial key values for each combined LFSR. 

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
A Modified Key Scheduling Algorithm for RC4
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Rivest Cipher 4 (RC4) is an efficient stream cipher that is commonly used in internet protocols. However, there are several flaws in the key scheduling algorithm (KSA) of RC4. The contribution of this paper is to overcome some of these weaknesses by proposing a new version of KSA coined as modified KSA . In the initial state of the array is suggested to contain random values instead of the identity permutation. Moreover, the permutation of the array is modified to depend on the key value itself. The proposed performance is assessed in terms of cipher secrecy, randomness test and time under a set of experiments with variable key size and different plaintext size. The results show that the RC4 with improves the randomness and secrecy with

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Publication Date
Sun Feb 24 2019
Journal Name
Iraqi Journal Of Physics
Adaptive inter frame compression using image segmented technique
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The computer vision branch of the artificial intelligence field is concerned with developing algorithms for analyzing video image content. Extracting edge information, which is the essential process in most pictorial pattern recognition problems. A new method of edge detection technique has been introduces in this research, for detecting boundaries.

           Selection of typical lossy techniques for encoding edge video images are also discussed in this research. The concentration is devoted to discuss the Block-Truncation coding technique and Discrete Cosine Transform (DCT) coding technique. In order to reduce the volume of pictorial data which one may need to store or transmit,

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Publication Date
Thu Nov 01 2018
Journal Name
International Journal Of Biomathematics
A non-conventional hybrid numerical approach with multi-dimensional random sampling for cocaine abuse in Spain
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This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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Publication Date
Tue Jan 30 2018
Journal Name
Iraqi Journal Of Science
A Secure Enhancement for Encoding/ Decoding data using Elliptic Curve Cryptography
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The Elliptic Curve Cryptography (ECC) algorithm meets the requirements for multimedia encryption since the encipher operation of the ECC algorithm is applied at points only and that offer significant computational advantages. The encoding/decoding operations for converting the text message into points on the curve and vice versa are not always considered a simple process. In this paper, a new mapping method has been investigated for converting the text message into a point on the curve or point to a text message in an efficient and secure manner; it depends on the repeated values in coordinate to establish a lookup table for encoding/ decoding operations. The proposed method for mapping process is&

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
A Realistic Aggregate Load Representation for A Distribution Substation in Baghdad Network
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Electrical distribution system loads are permanently not fixed and alter in value and nature with time. Therefore, accurate consumer load data and models are required for performing system planning, system operation, and analysis studies. Moreover, realistic consumer load data are vital for load management, services, and billing purposes. In this work, a realistic aggregate electric load model is developed and proposed for a sample operative substation in Baghdad distribution network. The model involves aggregation of hundreds of thousands of individual components devices such as motors, appliances, and lighting fixtures. Sana’a substation in Al-kadhimiya area supplies mainly residential grade loads. Measurement-based

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Bat Algorithm Based an Adaptive PID Controller Design for Buck Converter Model
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The aim of this paper is to design a PID controller based on an on-line tuning bat optimization algorithm for the step-down DC/DC buck converter system which is used in the battery operation of the mobile applications. In this paper, the bat optimization algorithm has been utilized to obtain the optimal parameters of the PID controller as a simple and fast on-line tuning technique to get the best control action for the system. The simulation results using (Matlab Package) show the robustness and the effectiveness of the proposed control system in terms of obtaining a suitable voltage control action as a smooth and unsaturated state of the buck converter input voltage of ( ) volt that will stabilize the buck converter sys

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