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 consumption of fresh fruits has increased nowadays due to the lifestyle of the consumers. Maintaining the quality and nutritional value of cut fruits during storage is difficult compared to whole fruits. Deterioration of internal and external quality usually occurs in freshly harvested fruits. It is necessary to use different techniques to maintain the quality and increase the shelf life of the freshly cut product. This research studied the effect of treating apple slices with cold plasma once and with filtered water again on quality characteristics (hardness, moisture content, sugar content, carbohydrate content, and color) after being stored for five days. The best treatment was determined using two different pressures of the plasma j
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This research dealt with the impact of internal control on tax performance using balanced scorecard indicators because of its special importance in improving tax performance and reform. The internal control system is a safety valve for senior management in all organizations, it plays an important role in the regularity and development of work and the fight against corruption To provide reliable and accurate data and information, follow up on compliance with laws, regulations and instructions. The aim of this research is to demonstrate how control affects tax performance and how to adapt internal control components to improve tax performance. In the General Authority for taxes and its branches,. The research resulted in a number of conclu
... Show MoreWith the advent of the globalization, the rapid development in technology and the intensity of competition companies attemptto maintain competition advantages and retain customers. The traditional methods in managerial accounting become irrelevance to achieve the objectives of these companies especially with the rapid changes in modern manufacturing environment .Thus there is a need to new tools in accounting such as lean accounting, which is considered as a costing method that support creating value for the customer by costing the entire value stream, eliminating waste in the accounting process, reduced lead time, improved quality, lowered time delivery and increased available capacity. Using value stream focuses not only on the waste&n
... Show MoreHeart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix
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Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E
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Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the
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For the graph , the behavior associated with to the majority of the graphical properties of this graph is covered in this article. The reflection of the capabilities of on the Ly constructions is one of the key ideas addressed throughout this paper. For instance, by this technique we can comprehend the mechanism via which groups of relatively tiny structure are exist within Ly.
Understanding the compatibility between spider silk and conducting materials is essential to advance the use of spider silk in electronic applications. Spider silk is tough, but becomes soft when exposed to water. Here we report a strong affinity of amine-functionalised multi-walled carbon nanotubes for spider silk, with coating assisted by a water and mechanical shear method. The nanotubes adhere uniformly and bond to the silk fibre surface to produce tough, custom-shaped, flexible and electrically conducting fibres after drying and contraction. The conductivity of coated silk fibres is reversibly sensitive to strain and humidity, leading to proof-of-concept sensor and actuator demonstrations.
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