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.
Designing Teaching Aids and Their Effects on Learning and Retaining Diving and Cartwheel on Floor Exercises in Women’s’ Artistic Gymnastics
The research aimed at designing teaching aids that develop and help retain diving and cartwheel for third year college of physical education and sport sciences students in women’s artistic gymnastics. In addition to that, the researchers aimed at identifying the effect of these aids on learning and retaining cartwheel and diving in floor exercises. The researchers used the experimental method. The subjects were (20) third year female students from the college of physical education and sport sciences/ university of Baghdad sections K and H. the main experiment lasted for
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Abstract
The research study about the empowerment as an independent variable, in which details include (training and improvement, incentives, information sharing, trust, and delegation), has also focused on the performance of the service organization as a dependent variable in all dimensions which include (improve work efficiency, building the core competencies, focus on the beneficiary of the service, increasing the feeling of satisfaction of the employees, and the organizational support commitment). The research has been based on the opinions of a chosen sample of 75 service officers of the Ministry of Interior who work at the General Directorate of Traffic. The research problem has been identified by t
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In the present investigation, 24 adult dipteran species with forensic importance belonging to 13 genera and 8 families that were collected from different localities of Iraq. The specimens were identified by different taxonomical keys; in addition the date and localities of collecting specimens were recorded.
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The present study includs the isolation and identification of Keratinophilic fungi in fresh water samples collected from Tigris river in Baghdad, Iraq. Samples were collected from different districts of Baghdad (Al-Rustumia, Madina Al-Teb, Al-Azamia, Al-Kadimia, Al-Dorha and Al-Kanah). The water samples were examined for keratinophilic fungi by the plating method culturing and Hair Baiting Technique. A total number of 18 genera are recorded, in which the Tigris water indicates an impressive diversity of fungi. A variety of fungal strains were isolated from river water, out of 814 fungal colonies, Aspergillus terrus (5.5%) was the most frequent species, followed by Asperg
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th
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