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Encryption Symmetric secret Key in Wireless Sensor Network Using AES Algorithm

      Wireless sensor network (WSN) security is an important component for protecting data from an attacker. For improving security, cryptography technologies are divided into two kinds: symmetric and asymmetric. Therefore, the implementation of protocols for generating a secret key takes a long time in comparison to the sensor’s limitations, which  decrease network throughput because they are based on an asymmetric method. The asymmetric algorithms are complex and decrease network throughput. In this paper, an encryption symmetric secret key in wireless sensor networks (WSN) is proposed. In this work, 24 experiments are proposed, which are encryption using the AES algorithm in the cases of 1 key, 10 keys, 25 keys, and 50 keys. In each experiment, two chains are combined by using a hash function (SHA-2) to produce secret keys. The Network Simulator Version 2 (NS2) was used to assess the network throughput for the generated key. The randomness of the suggested LWM method has been tested by using the Diehard statistical test and the Entropy test. The results of the tests show that the encryption secret keys have a high level of data randomness.

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Publication Date
Sun Apr 29 2018
Journal Name
Iraqi Journal Of Science
Orthogonal Generalized Symmetric Higher bi-Derivations on Semiprime Г-Rings .

In this paper a Г-ring M is presented. We will study the concept of orthogonal generalized symmetric higher bi-derivations on Г-ring. We prove that if M is a 2-torsion free semiprime    Г-ring ,  and  are orthogonal generalized symmetric higher bi-derivations  associated with symmetric higher bi-derivations   respectively for all n ϵN.

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Publication Date
Sun Oct 22 2023
Journal Name
Iraqi Journal Of Science
Mesomorphic Properties of Symmetric Hydrogen – Bonding Dimers Containing Chalcone Moiety

The work involves synthesis of a new homologous series of hydrogen bonding
liquid crystal dimers containing chalcone moiety. All the prepared compounds were
characterized by spectroscopic techniques such as FT – IR, 1H-NMR, 13C-NMR as
well as elemental analysis. All the synthesized dimers exhibited nematic and smectic
A phase. The mesophases behaviour and transitional temperatures were studied by
polarized microscopy and differential scanning calorimetry, and are discussed the
self- assemble of H-bonding donor and acceptor complexes

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network

 

The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

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Publication Date
Tue Jan 18 2022
Journal Name
Photonic Sensors
Arsenic Detection Using Surface Plasmon Resonance Sensor With Hydrous Ferric Oxide Layer
Abstract<p>The lethality of inorganic arsenic (As) and the threat it poses have made the development of efficient As detection systems a vital necessity. This research work demonstrates a sensing layer made of hydrous ferric oxide (Fe<sub>2</sub>H<sub>2</sub>O<sub>4</sub>) to detect As(III) and As(V) ions in a surface plasmon resonance system. The sensor conceptualizes on the strength of Fe<sub>2</sub>H<sub>2</sub>O<sub>4</sub> to absorb As ions and the interaction of plasmon resonance towards the changes occurring on the sensing layer. Detection sensitivity values for As(III) and As(V) were 1.083 °·ppb<sup>−1</sup> and 0.922 °·ppb<jats></jats></p> ... Show More
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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Identificatio n Of Key Factors Affecting Waste Management In Life Cycle Of The Construction Project By Using Delphi Technique

The problem of generated waste as a result of the implementation of construction projects, has  been aggravated recently because of construction activity experienced by the world, especially Iraq, which is going through a period of reconstruction, where construction waste represents (20-40%) of the total generated waste and has a negative effect on the environment and economic side of the project. In addition, the rate of consumpted  amounts of natural resources are estimated to be about 40% in the construction industry, so it became necessary to reduce waste and to be manage well. This study aims to identify the key factors affecting waste management through the various phases of the project, and this is accom

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Publication Date
Thu Aug 02 2012
Journal Name
International Journal Of Advanced Research In Computer Science
User Authentication based on Keystroke Dynamics Using Backpropagation Network

Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

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Publication Date
Tue Jan 17 2017
Journal Name
International Journal Of Science And Research (ijsr)
Publication Date
Sat Jan 01 2022
Journal Name
Proceedings Of International Conference On Computing And Communication Networks
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Comparison Study of Electromyography Using Wavelet and Neural Network

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Classifying Illegal Activities on Tor Network using Hybrid Technique

    With the freedom offered by the Deep Web, people have the opportunity to express themselves freely and discretely, and sadly, this is one of the reasons why people carry out illicit activities there. In this work, a novel dataset for Dark Web active domains known as crawler-DB is presented. To build the crawler-DB, the Onion Routing Network (Tor) was sampled, and then a web crawler capable of crawling into links was built. The link addresses that are gathered by the crawler are then classified automatically into five classes. The algorithm built in this study demonstrated good performance as it achieved an accuracy of 85%. A popular text representation method was used with the proposed crawler-DB crossed by two different supervise

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