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%.
In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf
... Show MoreIn this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.
To maintain a sustained competitive position in the contemporary environment of knowledge economy, organizations as an open social systems must have an ability to learn and know how to adapt to rapid changes in a proper fashion so that organizational objectives will be achieved efficiently and effectively. A multilevel approach is adopted proposing that organizational learning suffers from the lack of interest about the strategic competitive performance of the organization. This remains implicit almost in all models of organizational learning and there is little focus on how learning organizations achieve sustainable competitive advantage . A dynamic model that captures t
... Show MoreAutomatic recognition of individuals is very important in modern eras. Biometric techniques have emerged as an answer to the matter of automatic individual recognition. This paper tends to give a technique to detect pupil which is a mixture of easy morphological operations and Hough Transform (HT) is presented in this paper. The circular area of the eye and pupil is divided by the morphological filter as well as the Hough Transform (HT) where the local Iris area has been converted into a rectangular block for the purpose of calculating inconsistencies in the image. This method is implemented and tested on the Chinese Academy of Sciences (CASIA V4) iris image database 249 person and the IIT Delhi (IITD) iris
... Show MoreAbstract
The study seeks to use one of the techniques (Data mining) a (Logic regression) on the inherited risk through the use of style financial ratios technical analysis and then apply for financial fraud indicators,Since higher scandals exposed companies and the failure of the audit process has shocked the community and affected the integrity of the auditor and the reason is financial fraud practiced by the companies and not to the discovery of the fraud by the auditor, and this fraud involves intentional act aimed to achieve personal and harm the interests of to others, and doing (administration, staff) we can say that all frauds carried out through the presence of the motives and factors that help th
... Show MoreRecent research has shown that a Deoxyribonucleic Acid (DNA) has ability to be used to discover diseases in human body as its function can be used for an intrusion-detection system (IDS) to detect attacks against computer system and networks traffics. Three main factor influenced the accuracy of IDS based on DNA sequence, which is DNA encoding method, STR keys and classification method to classify the correctness of proposed method. The pioneer idea on attempt a DNA sequence for intrusion detection system is using a normal signature sequence with alignment threshold value, later used DNA encoding based cryptography, however the detection rate result is very low. Since the network traffic consists of 41 attributes, therefore we proposed the
... Show MoreObjectives of the study: The main objective of the study is to assess the prevalence of hypertension among
cardiac diseases patients and to fiend out relation ship between hypertension and cardiovascular diseases.
Methodology: A descriptive study, using interviewer and questionnaire technique was conducted on cardiac
diseases inpatients of clinic unite at Kirkuk and Azady hospitals from 17th ,June ,2012 to 1st, March , 2013.
Non – probability (purposive) sample of (148) adult patients, (81) females and (67) males with heart disease are
selected from inpatients of clinic unite at Kirkuk and Azady hospitals at kirkuk city. Questionnaire was
developed to assess the items which are related to heart disease patient's (Dise
Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
... Show MoreGiven a matrix, the Consecutive Ones Submatrix (C1S) problem which aims to find the permutation of columns that maximizes the number of columns having together only one block of consecutive ones in each row is considered here. A heuristic approach will be suggested to solve the problem. Also, the Consecutive Blocks Minimization (CBM) problem which is related to the consecutive ones submatrix will be considered. The new procedure is proposed to improve the column insertion approach. Then real world and random matrices from the set covering problem will be evaluated and computational results will be highlighted.