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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The current study aims to develop a proposed educational program based on augmented reality (AR) technology, in addition to assessing its effectiveness in developing research and historical imagination skills of the Humanities Track's female students at the secondary stage, as well as assessing the correlative and predictive relationships between the amount of growth for the two dependent variables. To achieve this, a secondary school in the city of Makkah Al-Mukarramah was chosen, and an available random sample of (30) female students from the study population was selected. The quasi-experimental approach was followed by this study, particularly one group design. In addition, two tools were used to collect study data, namely: a test of
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This research aims to apply the Performance Focused Activity Based Costing System in the consultant office of Al-Khwarizmi College of Engineering at the University of Technology for the purpose of measuring the cost of consulting services provided by these offices in order to reduce costs and their reflection in achieving profits. For the purpose of calculating costs accurately, and to test the hypothesis of the research, the research was applied in the office of the consultant of the College of Engineering Al-Khwarizm - University of Baghdad through the financial statement
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Background: Ankylosing spondylitis is a chronic inflammatory disease that mostly involves the spine and sacroiliac joints. It is associated with a decreased quality of life. Biological medicines such as infliximab and its biosimilar are the mainstay treatments for active ankylosing spondylitis.
Objective: The study objective was to conduct a pharmacoeconomic study comparing the cost-effectiveness of the reference infliximab with its biosimilar in ankylosing spondylitis patients visiting public hospitals.
Subjects and Method: This is a two-center pharmacoeconomic study performed at two large teaching governmental hospitals in Baghdad, Iraq, which s
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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