Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss function to enforce the proposed model in multiple classification, including five labels, one is normal and four others are attacks (Dos, R2L, U2L and Probe). Accuracy metric was used to evaluate the model performance. The proposed model accuracy achieved to 99.45%. Commonly the recognition time is reduced in the NIDS by using feature selection technique. The proposed DNN classifier implemented with feature selection algorithm, and obtained on accuracy reached to 99.27%.
This paper introduces a relationship between the independence of polynomials associated with the links of the network, and the Jacobian determinant of these polynomials. Also, it presents a way to simplify a given communication network through an algorithm that splits the network into subnets and reintegrates them into a network that is a general representation or model of the studied network. This model is also represented through a combination of polynomial equations and uses Groebner bases to reach a new simplified network equivalent to the given network, which may make studying the ability to solve the problem of network coding less expensive and much easier.
The present study aims at examining quantitatively the morphometric characteristics of Iziana Valley basin that is located in the northern part of Iraq; particularly in south of Erbil Governorate. This basin is considered one of the small sub-basins where its valleys run on formations of the Triple and Quadrant Ages, which are represented by the Bay Hassan formations, and the sediments and mixed sediments of the cliffs, respectively. The area of the Iziana basin amounts to (36.39 km2) whereas the percentage of its rotation reaches (0.17); a low percentage, which indicates that the basin diverges from the circular to the rectangular shape. The value of the elongation ratio of the basin reaches (0.38) while the terrain rat
... Show MoreThe issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator
... Show MoreIn this paper, we propose a new approach of regularization for the left censored data (Tobit). Specifically, we propose a new Bayesian group Bridge for left-censored regression ( BGBRLC). We developed a new Bayesian hierarchical model and we suggest a new Gibbs sampler for posterior sampling. The results show that the new approach performs very well compared to some existing approaches.
The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of
... Show MoreThis article investigates how an appropriate chaotic map (Logistic, Tent, Henon, Sine...) should be selected taking into consideration its advantages and disadvantages in regard to a picture encipherment. Does the selection of an appropriate map depend on the image properties? The proposed system shows relevant properties of the image influence in the evaluation process of the selected chaotic map. The first chapter discusses the main principles of chaos theory, its applicability to image encryption including various sorts of chaotic maps and their math. Also this research explores the factors that determine security and efficiency of such a map. Hence the approach presents practical standpoint to the extent that certain chaos maps will bec
... Show MoreIn the last decade, the web has rapidly become an attractive platform, and an indispensable part of our lives. Unfortunately, as our dependency on the web increases so programmers focus more on functionality and appearance than security, has resulted in the interest of attackers in exploiting serious security problems that target web applications and web-based information systems e.g. through an SQL injection attack. SQL injection in simple terms, is the process of passing SQL code into interactive web applications that employ database services such applications accept user input such as form and then include this input in database requests, typically SQL statements in a way that was not intende
... Show MoreSlow learning becomes a problem in the present , where it comprises ratio musnt ignore in every school . So , its one of education problems facing by parents and teachers .
Slow learning subject regard of new subject attract the attention in the last years of the 20th century where the attention was focusing on the other disabilities but the existence of number of healthy children suffering from Learning problems attract the attention of the researchers .
So , this study aims at recognizing the degree of self , concept among slow learner students and the differences significance of self concept according to sex and academic degree of parents variables.
Because there is not tool , the researcher build a
... Show Moreهدفت الدراسة الحالية الى التعرف ما اذا كان هناك تقبل اجتماعي للتلاميذ بطيئي من قبل اقرانهم العاديين؟ وكذلك معرفة ما اذا كان هناك فروق ذات دلالة في التقبل الاجتماعي بين افراد عينة الدراسة على وفق المتغيرات الاتية:
أ- العمر (9-13)
ب- الجنس (ذكور –اناث)
ج- المرحلة الدراسية
د- الحالة الاقتصادية (جيدة –متوسطة –جيدة جدا)
ولغرض تحقيق اه
... Show MoreFind extract This research aims to find out (after learning strategy cells in the development of critical thinking and reflective thinking at the fifth-grade students in the geographic literary material). And follow researcher Almhnj demo for the purpose of achieving the goals of current research and design on an experimental group and a control with a test group after me and adopted chose researcher sample Find a way Mqsidih students of junior high Kadhimiya Boys of the breeding Baghdad / Karkh II and to verify the effectiveness of the search coined researcher hypotheses following cases: - 1. No statistically significant between the mean scores of the experimental group and the students taught her students that strategy differences (lea
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