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.
This work is concerned with the study of the effect of cement types, particularly OPC and SRPC, which are the main cement types manufactured in Iraq. In addition, study the effect of mineral admixtures, which are HRM and SF on the resistance of high performance concrete (HPC) to internal sulphate attack. The HRM is used at (10%) and SF is used at (8 and 10)% as a partial replacement by weight of cement for both types. The percentages of sulphate investigated are (1,2 and 3)% by adding natural gypsum as a partial replacement by weight of fine aggregate. The tests carried out in this work are: compressive strength, flexural strength, ultrasonic pulse velocity, and density at the age of 7, 28, 90 and 120 days.
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... Show MoreThe aim of this study to identify patterns of cerebral control (right and left) for second grade students in the collage of physical education and sports science of the University of Baghdad, as well as identify the definition of theThe Effect of Using the Bybee Strategy(5ES) according to Brain Control Patterns in Learning a Kinetic Series on Floor exercises in Artistic Gymnastics for menمجلة الرياضة المعاصرةالمجلد 19 العدد 1 عام 2020effect using the (Bybee) strategy (5ES) according to brain control patterns inlearning a Kinetic series on floor exercises In artistic gymnastics for men, andidentify the best combination between the four research groups learn, use Finderexperimental method research sample consi
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In recent decades, drug modification is no longer unusual in the pharmaceutical world as living things are evolving in response to environmental changes. A non-steroidal anti-inflammatory drug (NSAID) such as aspirin is a common over-the-counter drug that can be purchased without medical prescription. Aspirin can inhibit the synthesis of prostaglandin by blocking the cyclooxygenase (COX) which contributes to its properties such as anti-inflammatory, antipyretic, antiplatelet and etc. It is also being considered as a chemopreventive agent due to its antithrombotic actions through the COX’s inhibition. However, the prolonged use of aspirin can cause heartburn, ulceration, and gastro-toxicity in children and adults. This review article hi
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Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab
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In this paper, we investigate and characterize the effects of multi-channel and rendezvous protocols on the connectivity of dynamic spectrum access networks using percolation theory. In particular, we focus on the scenario where the secondary nodes have plenty of vacant channels to choose from a phenomenon which we define as channel abundance. To cope with the existence of multi-channel, we use two types of rendezvous protocols: naive ones which do not guarantee a common channel and advanced ones which do. We show that, with more channel abundance, even with the use of either type of rendezvous protocols, it becomes difficult for two nodes to agree on a common channel, thereby, potentially remaining invisible to each other. We model this in
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Remote surveying of unknown bound geometries, such as the mapping of underground water supplies and tunnels, remains a challenging task. The obstacles and absorption in media make the long-distance telecommunication and localization process inefficient due to mobile sensors’ power limitations. This work develops a new short-range sequential localization approach to reduce the required amount of signal transmission power. The developed algorithm is based on a sequential localization process that can utilize a multitude of randomly distributed wireless sensors while only employing several anchors in the process. Time delay elliptic and frequency range techniques are employed in developing the proposed algebraic closed-form solution.
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This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio
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