Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse detection techniques using two DM classifiers (Interactive Dichotomizer 3 (ID3) classifier and Naïve Bayesian (NB) Classifier) to verify the validity of the proposed system in term of accuracy rate. A proposed HybD dataset used in training and testing the hybrid IDS. Feature selection is used to consider the intrinsic features in classification decision, this accomplished by using three different measures: Association rules (AR) method, ReliefF measure, and Gain Ratio (GR) measure. NB classifier with AR method given the most accurate classification results (99%) with false positive (FP) rate (0%) and false negative (FN) rate (1%).
One wide-ranging category of open source data is that referring to geospatial information web sites. Despite the advantages of such open source data, including ease of access and cost free data, there is a potential issue of its quality. This article tests the horizontal positional accuracy and possible integration of four web-derived geospatial datasets: OpenStreetMap (OSM), Google Map, Google Earth and Wikimapia. The evaluation was achieved by combining the tested information with reference field survey data for fifty road intersections in Baghdad, Iraq. The results indicate that the free geospatial data can be used to enhance authoritative maps especially small scale maps.
The achievements of the art that we know today are questioned in motives that differ from what art knew before, including dramatic artistic transformations, which he called modern art.
In view of the enormity of such a topic, its ramifications and its complexity, it was necessary to confine its subject to the origin of the motives of the transformations of its first pioneers, and then to stand on what resulted from that of the data of vision in composition and drawing exclusively, and through exploration in that, we got to know the vitality of change from the art of its time.
And by examining the ruling contemporary philosophical concepts and their new standards and their epistemological role in contemporary life, since they includ
This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera
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Various methods are utilized providing complexity for cryptosystem with the aim to increase the security and avoiding hacker attack. Hybrid cryptosystem is one of these cryptosystems which is used two types of cryptosystems and has many applications in data transmitted. This research, proposed a novel method that used power exponent instead of using the prime number directly and also providing complexity of asymmetric cryptosystems. This method has been applied theoretically in two public systems RSA and EL-Gamal. Power RSA and Power EL-Gamal are modified asymmetric cryptosystems, in which the power number is kept by the sender and the receiver. Moreover, we use group theory to prove that these cryptosystems work properly. Our exten
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Landlocked countries are displayed geopolitical new geo-political and intended to
countries that do not have sea views, a phenomenon present in four continents of the world
are: Africa, Europe, and Asia, and South America and the number arrived at the present time
to the (44) state the largest number of them in the continent it arrived in Africa (16) countries
in Asia (13) countries and Europe (13) In the State of South America two. This phenomenon
emerged due to the division of federations and empires and colonial treaties and others. But
the negative effects suffered by these countries may vary from one country to another, since
these countries in the continent of Europe, for example, is different from the same cou
Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica
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Background: Penetrating neck injuries are common problem in our country due to increasing violence, terrorist bombing and military operations.
These injuries are potentially life threating and need great attention and proper management.
Objective: The aim of this study is to focus on the importance of anatomical zonal classification of the neck in the management of penetrating injuries of the visceral compartment of the Neck.
Methods :70 patients with various injuries who were managed at causality unit and Otolaryngology department in Al-Kindy Teaching Hospital during aperiod from January 1st 2015 to October 31st 2015.
The study carried on those patient depending on proper clinical examination and their urgent management.
Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature
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