Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks can also be made with smart devices that connect to the Internet, which can be infected and used as botnets. They use Deep Learning (D.L.) techniques like Convolutional Neural Network (C.N.N.) and variants of Recurrent Neural Networks (R.N.N.), such as Long Short-Term Memory (L.S.T.M.), Bidirectional L.S.T.M., Stacked L.S.T.M., and the Gat G.R.U.. These techniques have been used to detect (DDoS) attacks. The Portmap.csv file from the most recent DDoS dataset, CICDDoS2019, has been used to test D.L. approaches. Before giving the data to the D.L. approaches, the data is cleaned up. The pre-processed dataset is used to train and test the D.L. approaches. In the paper, we show how the D.L. approach works with multiple models and how they compare to each other.
The research aims to evaluate Islamic electronic libraries and their service for downloading research and illustrated books, explaining their origins, features and types. The research was limited to the libraries available on the Internet that provide the service for downloading research and illustrated books. The researcher relied on the survey approach to identify the libraries and a sample of them (20 libraries) was selected. For the purpose of evaluating it according to five criteria related to the preparation and publication of Islamic electronic libraries (the responsible party, the goals and objectives, the year, the services it provides, the sections and subject specializations of its contents) and five criteria related to the servi
... Show MoreSoftware Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification
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Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
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It is often needed to have circuits that can display the decimal representation of a binary number and specifically in this paper on a 7-segment display. In this paper a circuit that can display the decimal equivalent of an n-bit binary number is designed and it’s behavior is described using Verilog Hardware Descriptive Language (HDL). This HDL program is then used to configure an FPGA to implement the designed circuit.
Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a
... Show MoreFace Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a
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Thrust blocks and restraint joints are the two most popular methods of counteracting the thrust force that generated at pipe fittings (bends, Tee, wye, reducers, dead ends, etc…). Both systems perform the same function, which is to prevent the joints from separating from the pipes. The aim of the study is to review previous studies and scientific theories related to the study and design of thrust blocks and restraint joints to study the behavior of both systems under thrust force and to study the factors and variables that affect the behavior of these systems. The behavior of both systems must be studied because they cannot be abandoned, as each system has conditions whose use is more feasible, scientific, and economic
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CD40 is a type 1 transmembrane protein composed of 277 amino acids, and it belongs to the tumor necrosis factor receptor (TNFR) superfamily. It is expressed in a variety of cell types, including normal B cells, macrophages, dendritic cells, and endothelial cells, as a costimulatory molecule. This study aims to summarize the CD40 polymorphism effect and its susceptibility to immune-related disorders. The CD40 gene polymorphisms showed a significant association with different immune-related disorders and act as a risk factor for increased susceptibility to these diseases.
Absence or hypoplasia of the internal carotid artery (ICA) is a rare congenital anomaly that is mostly unilateral and highly associated with other intracranial vascular anomalies, of which saccular aneurysm is the most common. Blood flow to the circulation of the affected side is maintained by collateral pathways, some of which include the anterior communicating artery (Acom) as part of their anatomy. Therefore, temporary clipping during microsurgery on Acom aneurysms in patients with unilateral ICA anomalies could jeopardize these collaterals and place the patient at risk of ischemic damage. In this paper, we review the literature on cases with a unilaterally absent ICA associa
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