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 investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
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تعد مراجعة النظير واحدة من الأســاليب الحديثة فــي مجال الرقابة والتدقيق ونشــأة كأداة لقياس مــدى فاعليــة الرقابــة علــى الجــودة هو لبنة أساسية في إدارة الجودة الشاملة ووسيلة لتحســين أدوات الرقابــة المعمول بها، وللتحقق من مدى الانسجام بين المعايير الدولية للأجهزة العليا للرقابة المالية والمحاسبة والاجراءات المعمول بها من قبل الاجهزة العليا للرقابة وعليه فأن مراجعة النظير أداة تستخدم ف
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The aim of the current research is to prepare an integrated learning program based on mathematics standards for the next generation of the NYS and to investigate its impact on the development of the teaching performance of middle school mathematics teachers and the future thinking skills of their students. To achieve the objectives of the research, the researcher prepared a list of mathematics standards for the next generation, which were derived from a list of standards. He also prepared a list of the teaching competencies required for middle school mathematics teachers in light of the list of standards, as well as clarified the foundations of the training program and its objectives and the mathematical
... Show MoreThis study concluded detection of Toxoplasma gondii in milk, immunologically by using Elisa and nested PCR)nPCR (based on B1 gene, also to investigate the effect of toxoplasmosis, parity, breed and flock on some milk composition in the Iraqi local and Shami goats in the middle of Iraq. A total of 80 milk samples of the lactating goats were collected. Results of this study showed the prevalence of Toxoplasmosis was 21.25% and 28.75% by Elisa and nPCR respectively without significant differences. The sensitivity of Elisa was a low (30.43%) whereas the specificity was a high (82.45%). The degree of agreement estimated by Kappa coefficient revealed a slight agreement (0.14) between two methods. The results indicated that goats infected
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After baking the flour, azodicarbonamide, an approved food additive, can be converted into carcinogenic semicarbazide hydrochloride (SEM) and biurea in flour products. Thus, determine SEM in commercial bread products is become mandatory and need to be performed. Therefore, two accurate, precision, simple and economics colorimetric methods have been developed for the visual detection and quantitative determination of SEM in commercial flour products. The 1st method is based on the formation of a blue-coloured product with λmax at 690 nm as a result of a reaction between the SEM and potassium ferrocyanide in an acidic medium (pH 6.0). In the 2nd method, a brownish-green colored product is formed due to the reaction between the SEM and phosph
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
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Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T
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Bacteriocin is an important antimicrobial peptide that can be used in industrial and medical fields due to its characteristics of antibacterial, food preservation and anticancer activities. Fifty isolates of Bacillus sp were collected from different soil samples which were already recognized via morphological and biochemical identification process. The isolates were screened for bacteriocin production effective against Staphylococcus spp in order to select the highest producing isolate. The isolate NK16 showed the maximum bacteriocin production (80 AU/ml) which was further characterized as Bacillus subtilis NK 16 through using API identification system (API 20E and API 50CHB). Then, next step was to detect the optimal conditions for maximum
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The purpose of this research shed light on the analysis of the relationship between the knowledge gap and the strategic performance gap and diagnose the level of impact this relationship in building a learning organization, and sought search to achieve a number of goals, cognitive and Applied been tested nature of the relationship and effect between variables in a sample size (62) of the managers of banks civil in Baghdad (Baghdad, Gulf, Assyria, Union, Elaf) and focused research problem in question is bold is whether the analysis of the relationship between the knowledge gap and the performance gap strategic leads to recognize organizations need to shift to organizations educated, either in the side of the field was the pr
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