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Keystroke Dynamics Authentication based on Naïve Bayes Classifier
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Authentication is the process of determining whether someone or something is,
in fact, who or what it is declared to be. As the dependence upon computers and
computer networks grows, the need for user authentication has increased. User’s
claimed identity can be verified by one of several methods. One of the most popular
of these methods is represented by (something user know), such as password or
Personal Identification Number (PIN). Biometrics is the science and technology of
authentication by identifying the living individual’s physiological or behavioral
attributes. Keystroke authentication is a new behavioral access control system to
identify legitimate users via their typing behavior. The objective of this paper is to
provide user authentication based on keystroke dynamic in order to avoid un
authorized user access to the system. Naive Bayes Classifier (NBC) is applied for
keystroke authentication using unigraph and diagraph keystroke features. The
unigraph Dwell Time (DT), diagraph Down-Down Time (DDT) features, and
combination of (DT and DDT) are used. The results show that the combination of
features (DT and DDT) produces better results with low error rate as compared
with using DT or DDT alone.

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Publication Date
Wed Feb 16 2022
Journal Name
Iraqi Journal Of Science
Efficient method to Recognition of Anemia Images based on Moment Invariants and Decision tree classifier
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Anemia is one of the common types of blood diseases, it lead to lack of number of RBCs (Red Blood Cell) and amount hemoglobin level in the blood is lower than normal.
In this paper a new algorithm is presented to recognize Anemia in digital images based on moment variant. The algorithm is accomplished using the following phases: preprocessing, segmentation, feature extraction and classification (using Decision Tree), the extracted features that are used for classification are Moment Invariant and Geometric Feature.
The Best obtained classification rates was 84% is obtained when using Moment Invariants features and 74 % is obtained when using Geometric Feature. Results indicate that the proposed algorithm is very effective in detect

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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Entropy-Based Feature Selection using Extra Tree Classifier for IoT Security
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      The Internet of Things (IoT) is a network of devices used for interconnection and data transfer. There is a dramatic increase in IoT attacks due to the lack of security mechanisms. The security mechanisms can be enhanced through the analysis and classification of these attacks. The multi-class classification of IoT botnet attacks (IBA) applied here uses a high-dimensional data set. The high-dimensional data set is a challenge in the classification process due to the requirements of a high number of computational resources. Dimensionality reduction (DR) discards irrelevant information while retaining the imperative bits from this high-dimensional data set. The DR technique proposed here is a classifier-based fe

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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Comparison of Maximum Likelihood and some Bayes Estimators for Maxwell Distribution based on Non-informative Priors
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In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of B

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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Bayes and Non-Bayes Estimation Methods for the Parameter of Maxwell-Boltzmann Distribution
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In this paper, point estimation for parameter ? of Maxwell-Boltzmann distribution has been investigated by using simulation technique, to estimate the parameter by two sections methods; the first section includes Non-Bayesian estimation methods, such as (Maximum Likelihood estimator method, and Moment estimator method), while the second section includes standard Bayesian estimation method, using two different priors (Inverse Chi-Square and Jeffrey) such as (standard Bayes estimator, and Bayes estimator based on Jeffrey's prior). Comparisons among these methods were made by employing mean square error measure. Simulation technique for different sample sizes has been used to compare between these methods.

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
Authentication of Digital Video Encryption
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The security of multimedia data becoming important spatial data of monitoring systems that contain videos prone to attack or escape via the internet, so to protect these videos used proposed method combined between encryption algorithm and sign algorithm to get on authenticated video. The proposed encryption algorithm applied to secure the video transmission by encrypt it to become unclear. This done by extract video to frames and each frame separate to three frames are Red, Green, and Blue, this frames encrypt by using three different random keys that generated by a function for generating random numbers, as for sign algorithm applied for authentication purpose that enable the receiver from sure of the identity of the sender and provide

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
A Nonlinear MIMO-PID Neural Controller Design for Vehicle Lateral Dynamics model based on Modified Elman Neural Network
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This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

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Publication Date
Wed Mar 28 2018
Journal Name
Iraqi Journal Of Science
Advanced Password Authentication Protection by Hybrid Cryptography & Audio Steganography
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     Data transmission in public communication system is not safe since of interception and improper manipulation by attacker. So, the attractive solution for these problems is to design high secure system that reduce the ability of attacker from getting sensitive information such as (account ID, passwords, etc.). The best way is combine two high secure techniques: steganography technique, which is the method of hiding any secret information like data, password and image behind any cover file and cryptography, which is convert the data to unreadable data. This paper suggests a crypto-stego authentication method to provide a highly secured authentication. The proposed method is utilized audio steganography and AES Cryp

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Publication Date
Mon Aug 20 2018
Journal Name
Physical Review E
Dynamical density-functional-theory-based modeling of tissue dynamics: Application to tumor growth
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Publication Date
Sun Jun 01 2008
Journal Name
Baghdad Science Journal
The Writer Authentication by Using Syllables Frequency
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An approach is depended in the recent years to distinguish any author or writer from other by analyzing his writings or essays. This is done by analyzing the syllables of writings of an author. The syllable is composed of two letters; therefore the words of the writing are fragmented to syllables and extract the most frequency syllables to become trait of that author. The research work depend on analyzed the frequency syllables in two cases, the first, when there is a space between the words, the second, when these spaces are ignored. The results is obtained from a program which scan the syllables in the text file, the performance is best in the first case since the sequence of the selected syllables is higher than the same syllables in

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Publication Date
Wed Apr 24 2019
Journal Name
Aerosol Science And Technology
Effect of axial eccentricity on the performance of a cylindrical differential mobility classifier
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