The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines Grey Wolf Optimization (GWO) with Borderline-SMOTE. Particle Swarm Optimization (PSO) was used to select the most important features that provide the greatest amount of information for training the first layer, which was built using deep learning techniques, and linking them in a hybrid manner that combines a Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) and the Attention mechanism. The proposed model was evaluated using two different types of datasets: the CICIOT2023 dataset, which is characterized by its large size and significant variation in the number of attacks, and the UNSW-NB15 dataset, which is characterized by its simplicity and less imbalance compared to the first dataset, to prepare and generalize the system across multiple environments. The proposed class showed binary classification results with an accuracy of 0.94, an Area Under the Curve (AUC) of 0.93, an optimized F1-score of 0.338, and a Matthews Correlation Coefficient (MCC) of 0.324 at the best threshold on the CICIoT2023 dataset. It also achieved an accuracy of approximately 0.96, an AUC of 0.985, and an MCC of over 0.82 on the UNSW-NB15 dataset. These results confirmed the construction of a strong and resilient layer, preparing the foundation for a robust hierarchical offside detection system.
The research presents the reliability. It is defined as the probability of accomplishing any part of the system within a specified time and under the same circumstances. On the theoretical side, the reliability, the reliability function, and the cumulative function of failure are studied within the one-parameter Raleigh distribution. This research aims to discover many factors that are missed the reliability evaluation which causes constant interruptions of the machines in addition to the problems of data. The problem of the research is that there are many methods for estimating the reliability function but no one has suitable qualifications for most of these methods in the data such
A second-order sliding mode control is used for high-order uncertain plants using equivalent control approach to improve the performance of control systems. They combine backstepping with quasi-continuous controller and twisting controllers. This paper considers a two of the most popular controllers that are used to solve the nonlinearities problem which are the backstepping quasi-continuous control (BQCC) and backstepping twisting controllers to control the angular velocity of a hydraulic motor to improve tracking performance and robustness to uncertainties. For the system dynamics, a linear state feedback with suitable high gain was designed as the virtual controller, where steady state error can be made arbitrarily small according to the
... Show MoreMicro-perforated panel (MPP) absorber is increasingly gaining popularity as an alternative sound absorber in buildings compared to the well-known synthetic porous materials. A single MPP has a typical feature of a Helmholtz resonator with a high amplitude of absorption but a narrow absorption frequency bandwidth. To improve the bandwidth, a single MPP can be cascaded with another single MPP to form a double-layer MPP. This paper proposes the introduction of inhomogeneous perforation in the double-layer MPP system (DL-iMPP) to enhance the absorption bandwidth of a double-layer MPP. Mathematical models are proposed using the equivalent electrical circuit model and are validated with experiments with good agreement. It is revealed that the DL-
... Show MoreThe current research aims to identify the effect of the learning mastery strategy using interactive learning as a therapeutic method on the achievement of secondary school students in mathematics. To achieve the research objective, the researcher selected second-grade middle school students at Al-Haybah Intermediate School for Boys and determined his research sample, which consisted of (77) students distributed into two sections: Section (A) the experimental group, with (38) students, and Section (B) the control group, with (39) students. The statistical equivalence of the two research sample groups was confirmed in the variables (intelligence test, previous achievement, and previous knowledge test). The researchers chose the par
... Show MoreThe predilection for 5G telemedicine networks has piqued the interest of industry researchers and academics. The most significant barrier to global telemedicine adoption is to achieve a secure and efficient transport of patients, which has two critical responsibilities. The first is to get the patient to the nearest hospital as quickly as possible, and the second is to keep the connection secure while traveling to the hospital. As a result, a new network scheme has been suggested to expand the medical delivery system, which is an agile network scheme to securely redirect ambulance motorbikes to the nearest hospital in emergency cases. This research provides a secured and efficient telemedicine transport strategy compatible with the
... Show MoreDeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio
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