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Articles 1 - 4 of 4
Full-Text Articles in Computer Engineering
Breast Tissue Tumor Detection Using Microstrip Patch Antenna With Defected Ground Structure, Nihal F. F. Areed, Hamdi Ahmed El Mikati, Laila T. Rakha
Breast Tissue Tumor Detection Using Microstrip Patch Antenna With Defected Ground Structure, Nihal F. F. Areed, Hamdi Ahmed El Mikati, Laila T. Rakha
Mansoura Engineering Journal
This work proposes a slotted microstrip patch antenna with an inset feed and defective ground structure (DGS). The proposed antenna is built with Roger-RT/5880 (Ԑr=2.2) as the substrate material for X-band application with a resonant frequency of 10 GHz. The proposed design has been simulated using Finite Element Method (FEM) and the results of bandwidth and gain read about 700MHz and 8dB; respectively. The suggested design is compared with previously published equivalent designs in light of the most recent research. The comparison reveal that that the suggested design with tuned dimensions offers higher gain and wider bandwidth than what has …
Detection Optimization Of Rare Attacks In Software-Defined Network Using Ensemble Learning, Ahmed M. El-Shamy, Nawal A. El-Fishawy, Gamal M. Attiya, Mokhtar Ahmed
Detection Optimization Of Rare Attacks In Software-Defined Network Using Ensemble Learning, Ahmed M. El-Shamy, Nawal A. El-Fishawy, Gamal M. Attiya, Mokhtar Ahmed
Mansoura Engineering Journal
Software-defined networking (SDN) is a highly flexible architecture that automates and facilitates network configuration and management. Intrusion detection systems (IDS) are becoming essential components in the network to detect malicious attacks and suspicious activities by continuously monitoring network traffic. Integration between SDN and machine learning (ML) techniques is extensively used to build an effective IDS against all potential cyber-attacks that aim at breaking the network security policy and stealing valuable data. Implementing an IDS based on SDN and ML has the advantage of managing traffic dynamically and fully autonomously to provide high protection against security threats. The main objective of …
Proposed Mitigation Framework For The Internet Of Insecure Things, Mahmoud M. Elgindy, Sally M. Elghamrawy, Ali I. El-Desouky
Proposed Mitigation Framework For The Internet Of Insecure Things, Mahmoud M. Elgindy, Sally M. Elghamrawy, Ali I. El-Desouky
Mansoura Engineering Journal
Intrusion detection systems IDS are increasingly utilizing machine learning methods. IDSs are important tools for ensuring the security of network data and resources. The Internet of Things (IoT) is an expanding network of intelligent machines and sensors. However, they are vulnerable to attackers because of the ubiquitous and extensive IoT networks. Datasets from intrusion detection systems (IDS) have been analyzed deep learning methods such as Bidirectional long-short term memory (BiLSTM). This research presents an BiLSTM intrusion detection framework with Principal Component Analysis PCA (PCA-LSTM-IDS). The PCA-LSTM-IDS is comprised of two layers: extracting layer which using PCA, and the anomaly BiLSTM …
Enhanced Load Balancing Based On Hybrid Artificial Bee Colony With Enhanced Β-Hill Climbing In Cloud, Maha Zeedan, Gamal Attiya, Nawal El-Fishawy
Enhanced Load Balancing Based On Hybrid Artificial Bee Colony With Enhanced Β-Hill Climbing In Cloud, Maha Zeedan, Gamal Attiya, Nawal El-Fishawy
Mansoura Engineering Journal
This paper proposes enhanced load balancer based artificial bee colony and β-Hill climbing for improving the performance metrics such as response time, processing cost, and utilization to avoid overloaded or under loaded situations of virtual machines. In this study, the suggested load balancer is called enhanced load balancing based on hybrid artificial bee colony with enhanced β-Hill climbing (ELBABCEβHC) to improve the response time, processing cost and the resource utilization. Our proposed approach starts by ranking the task then the greedy randomized adaptive search procedure (GRASP) is used in initializing populations. Further, the binary artificial bee colony (BABC) enhanced with …