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Adaptive Cloud Intrusion Detection System Based on Pruned Exact Linear Time Technique

Computers, Materials & Continua 2024年第6期79卷 3725-3756页

作者： Widad Elbakri Maheyzah Md.Siraj bander ali.saleh al-ri.y Sultan Noman Qasem Tawfik al-Hadhrami Faculty of Computing Universiti Teknologi MalaysiaJohor BahruJohor81310Malaysia Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia School of Science and Technology Nottingham Trent UniversityNottinghamNG118NSUK

Cloud computing environments,characterized by dynamic scaling,distributed architectures,and complex work-loads,are increasingly targeted by malicious *** threats encompass unauthorized access,data breaches,denial-of-service attacks,and evolving malware *** securi.y solutions often struggle with the dynamic nature of cloud environments,highlighting the need for robust Adaptive Cloud Intrusion Detection Systems(CIDS).Existing adaptive CIDS solutions,while offering improved detection capabilities,often face limitations such as reliance on approximations for change point detection,hindering their precision in identifying *** can lead to missed attacks or an abundance of false alarms,impacting overall securi.y *** address these challenges,we propose ACIDS(Adaptive Cloud Intrusion Detection System)-*** novel Adaptive CIDS framework leverages the Pruned Exact Linear Time(PELT)algorithm and a Support Vector Machine(SVM)for enhanced accuracy and ***-PELT comprises four key components:(1)Feature Selection:Utilizing a hybrid harmony search algorithm and the symmetrical uncertainty filter(HSO-SU)to identify the most relevant features that effectively differentiate between normal and anomalous network traffic in the cloud environment.(2)Surveillance:Employing the PELT algorithm to detect change points within the network traffic data,enabling the identification of anomalies and potential securi.y threats with improved precision compared to existing approaches.(3)Training Set:Labeled network traffic data forms the training set used to train the SVM classifier to distinguish between normal and anomalous behaviour patterns.(4)Testing Set:The testing set evaluates ACIDS-PELT’s performance by measuring its accuracy,precision,and recall in detecting securi.y threats within the cloud *** evaluate the performance of ACIDS-PELT using the NSL-KDD benchmark *** results demonstrate that ACIDS-PELT outperf

关键词： Adaptive cloud IDS harmony search distributed denial of service(DDoS) PELT machine learning SVM ISOTCID NSL-KDD

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A Deep Learning Approach for Landmines Detection Based on Airborne Magnetometry Imaging and Edge Computing

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 2117-2137页

作者： Ahmed Barnawi Krishan Kumar Neeraj Kumar bander alzahrani Amal almansour Faculty of Computing and Information Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyDeemed to be UniversityPatialaIndia

Landmines continue to pose an ongoing threat in various regions around the world,with countless buried landmines affecting numerous human *** detonation of these landmines results in thousands of casualties reported worldwide ***,there is a pressing need to employ diverse landmine detection techniques for their *** effective approach for landmine detection is UAV(Unmanned Aerial Vehicle)based AirborneMagnetometry,which identifies magnetic anomalies in the local terrestrial magnetic *** can generate a contour plot or heat map that visually represents the magnetic field *** the effectiveness of this approach,landmine removal remains a challenging and resource-intensive task,fraughtwith *** computing,on the other hand,can play a crucial role in critical drone monitoring applications like landmine *** processing data locally on a nearby edge server,edge computing can reduce communication latency and bandwidth requirements,allowing real-time analysis of magnetic field *** enables faster decision-making and more efficient landmine detection,potentially saving lives and minimizing the risks involved in the ***,edge computing can provide enhanced securi.y and privacy by keeping sensitive data close to the source,reducing the chances of data exposure during *** paper introduces the MAGnetometry Imaging based Classification System(MAGICS),a fully automated UAV-based system designed for landmine and buried object detection and *** have developed an efficient deep learning-based strategy for automatic image classification using magnetometry dataset *** simulating the proposal in various network scenarios,we have successfully detected landmine signatures present in themagnetometry *** trained models exhibit significant performance improvements,achieving a maximum mean average precision value of 97.8%.

关键词： CNN deep learning landmine detection magnetometer mean average precision UAV

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***:Hybrid Deep Learning for Enhancing IoT Network Intrusion Detection

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Computers, Materials & Continua 2021年第12期69卷 3945-3966页

作者： Ziadoon K.Maseer Robiah yusof Salama A.Mostafa Nazrulazhar Bahaman Omar Musa bander ali.saleh al-ri.y Faculty of Information and Communication Technology Universiti Teknikal MalaysiaMelaka76100Malaysia Center of Intelligent and Autonomous Systems Faculty of Computer Science and Information TechnologyUniversiti Tun Hussein Onn MalaysiaJohor86400Malaysia Faculty of Business and Technology UNITAR International UniversitySelangor47301Malaysia School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaJohor81310Malaysia

With an increasing number of services connected to the internet,including cloud computing and Internet of Things(IoT)systems,the prevention of cyberattacks has become more challenging due to the high dimensionality of the network traffic data and access ***,researchers have suggested deep learning(DL)algorithms to define intrusion features through training empirical data and learning anomaly patterns of ***,due to the high dynamics and imbalanced nature of the data,the existing DL classifiers are not completely effective at distinguishing between abnormal and normal behavior line connections for modern ***,it is important to design a self-adaptive model for an intrusion detection system(IDS)to improve the detection of ***,in this paper,a novel hybrid weighted deep belief network(HW-DBN)algorithm is proposed for building an efficient and reliable IDS(***)model to detect existing and novel *** HW-DBN algorithm integrates an improved Gaussian–Bernoulli restricted Boltzmann machine(Deep GB-RBM)feature learning operator with a weighted deep neural networks(WDNN)*** CICIDS2017 dataset is selected to evaluate the *** model as it contains multiple types of attacks,complex data patterns,noise values,and imbalanced *** have compared the performance of the *** model with three recent *** results show the *** model outperforms the three other models by achieving a higher detection accuracy of 99.38%and 99.99%for web attack and bot attack scenarios,***,it can detect the occurrence of low-frequency attacks that are undetectable by other models.

关键词： Cyberattacks internet of things intrusion detection system deep learning neural network supervised and unsupervised deep learning

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Reduced graphene oxide supersonically sprayed on wearable fabric and decorated with iron oxide for supercapacitor applications

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Journal of Materials Science & Technology 2021年第23期82卷 47-56页

作者： ali aldalbahi Edmund Samuel bander S.alotaibi Hany El-Hamshary Sam S.yoon Department of Chemistry College of ScienceKing Saud UniversityRiyadh11451Saudi Arabia School of Mechanical Engineering Korea UniversitySeoul136-713Republic of Korea

We demonstrate the fabrication of wearable supercapacitor *** electrodes were applied to wearable fabric by supersonically spraying the fabric with reduced graphene oxide(r GO)followed by decoration with iron oxide(Fe_(2)O_(3))nanoparticles via a hydrothermal *** integration of iron oxide with r GO flakes on wearable fabric demonstrates immense potential for applications in high-energystorage *** synergetic impact of the intermingled r GO flakes and Fe_(2)O_(3) nanoparticles enhances the charge transport within the composite electrode,ultimately improving the overall electrochemical *** advantage of the porous nature of the fabric,electrolyte diffusion into the active r GO and Fe_(2)O_(3) materials was significantly enhanced and subsequently increased the electrochemical interfacial *** effect of the Fe_(2)O_(3) concentration on the overall electrochemical performance was *** optimal composition yields a specific capacitance of 360 F g^(-1) at a current density of 1 Ag^(-1) with a capacitance retention rate of 89%after 8500 galvanostatic cycles,confirming the long-term stability of the Fe_(2)O_(3)/r GO fabric electrode.

关键词： Supersonic spraying Conductive textile Wearable energy devices Reduced graphene oxide Iron oxide Supercapacitor

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Maximum Likelihood Estimation for Generalized Pareto Distribution under Progressive Censoring with Binomial Removals

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Open Journal of Statistics 2012年第4期2卷 420-423页

作者： bander al-Zahrani Statistics Department Faculty of Sciences King Abdulaziz University P.O. Box 80203 Jeddah 21589 Saudi Arabia

The paper deals with the estimation problem for the generalized Pareto distribution based on progressive type-II censoring with random removals. The number of components removed at each failure time is assumed to follow a binomial distribution. Maximum likelihood estimators and the asymptotic variance-covariance matrix of the estimates are obtained. Finally, a numerical example is given to illustrate the obtained

关键词： Pareto Distribution Binomial Removal Progressive Censoring Maximum Likelihood Estimator

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A Secure Key Agreement Scheme for Unmanned Aerial Vehicles-Based Crowd Monitoring System

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Computers, Materials & Continua 2022年第3期70卷 6141-6158页

作者： bander alzahrani Ahmed Barnawi Azeem Irshad Areej alhothali Reem alotaibi Muhammad Shafiq Faculty of Computing and Information Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science and Software Engineering International Islamic University IslamabadPakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Unmanned aerial vehicles(UAVs)have recently attractedwidespread attention in civil and commercial *** example,UAVs(or drone)technology is increasingly used in crowd monitoring solutions due to its wider air footprint and the ability to capture data in real ***,due to the open atmosphere,drones can easily be lost or captured by attackers when reporting information to the crowd management *** addition,the attackers may initiate malicious detection to disrupt the crowd-sensing communication ***,securi.y and privacy are one of the most significant challenges faced by drones or the Internet of Drones(IoD)that supports the Internet of Things(IoT).In the literature,we can find some authenticated key agreement(AKA)schemes to protect access control between entities involved in the IoD ***,the AKA scheme involves many vulnerabilities in terms of securi.y and *** this paper,we propose an enhancedAKAsolution for crowdmonitoring applications that require secure communication between drones and controlling *** scheme supports key securi.y features,including anti-forgery attacks,and confirms user *** securi.y characteristics of our scheme are analyzed byNS2 simulation and verified by a random oracle *** simulation results and proofs show that the proposed scheme sufficiently guarantees the securi.y of crowd-aware communication.

关键词： IoT unmanned aerial vehicles authentication crowd monitoring

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Improvement of Early Maturing and Climate Resilient Chickpea (Cicer arietinum L.) Cultivars Suitable for Multiple Environments in Bangladesh

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Phyton-International Journal of Experimental Botany 2023年第3期92卷 883-899页

作者： Aktar-Uz-Zaman Ariful Islam Shahin Iqbal Jahangir alam Debashish Sarkar bander albogami Ahmed Gaber Akbar Hossain Pulses Research Centre Bangladesh Agricultural Research InstituteIshurdiPabna6600Bangladesh On-Farm Research Division Bangladesh Agricultural Research InstitutePabna6600Bangladesh Department of Biology College of ScienceTaif UniversityTaif21944Saudi Arabia Division of Soil Science Bangladesh Wheat and Maize Research InstituteDinajpur5200Bangladesh

Ensuring food securi.y for the rapidly increasing population and changing climatic scenarios are requisites for exploiting the genetic divergence of food crops.A study was undertaken to sort out an early maturing chickpea variety for fitting easily between rice-rice cropping systems in the Eastern Indo-Gangetic Plain of *** trial was comprised of eight elite lines of chickpea and executed at various localities in Bangladesh from 2014–15 to 2017–*** result explored the chickpea genotype,BAri Chola-11 remained superior to the rest of the elite genotypes for having a short maturi.y period(100–106 days),and lesser days to 50%flowering(47–55 days).The same genotype was recorded to have robust vegetative and reproductive yield attributes including plant height(49–57 cm),podsplant−1(37–50),and optimum 100 seed weight(19.5–20.6 g).Owing to better yield attributes,BAri Chola-11 resulted in the maximum seed yield(1200–1500 kg ha-1)of chickpea and might be recommended for general adoption in the region for boosting nutritional securi.y status through improved productivity under changing climate.

关键词： Short-duration variety multi-location yield trial high yielding variety GGE biplot analysis preliminary yield trial super early type

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The Role of Imaging in Examining Neurological Disorders;Assessing Brain, Stroke, and Neurological Disorders Using CT and Mri Imaging

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Advances in Computed Tomography 2020年第1期9卷 1-11页

作者： Shoaa G. Shetewi bander S. al Mutairi Saeed M. Bafaraj Department of Radiology King Abdulaziz University Hospital Jeddah KSA Faculty of Applied Medical Sciences Department of Diagnostic Radiology King Abdulaziz University Jeddah KSA

Background: Neurological disorder is identified as a severe cause of mortality among the patients. Given the severi.y of the disorder, various tools have been developed for the effective scanning of the symptoms and causes. Objective: The study intends to compare the two advanced neuroimaging tools i.e. computed tomography (CT) and magnetic resonance imaging (Mri) for assessing the patients of the possible brain, stroke, and neurological disorders concern their neurological symptoms and signs. Method: The retrospective study was conducted and medical records of 151 patients were assessed statistically. Chi-square test was applied to the collected data. Results: The results of the study provided that multiple seizures (15.2%) served as the major cause of examination, followed by a headache (9.9%), visual complaint (7.9%), single seizure (5.3%), gait abnormality (3.3%) and altered consciousness (2.6%);whereas, speech difficulty remained low (1.3%). CT scan findings of the patients reported parieto-temporal area and development of acute hypo densities as the prime concerns, where its results remained insignificant (0.29). Using Mri, unremarkable Mri was majorly reported, followed by lateralized to one side, stable Mri feature, bilateral symptoms, and ischemic disease. The results of Mri were significant (0.00). Conclusion: The study concludes that magnetic resonance imaging is more effective for the evaluation of the neurological disorders as compared to CT scan.

关键词： CT Scan Mri Neurological Disorder Brain Stroke

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Managements of Special Health Care Needs Patients from Dental Assistant Point

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International Journal of Clinical Medicine 2023年第2期14卷 59-64页

作者： Abdullah M. G. al Enazi Dalal Khalaf al Enazi Haya Nasser al Duaida Ashwag bander al Bakheet Mashael Muteb al Ghobain Abeer Salem al Harbi Department of Laboratory and Pathology King Abdulaziz Medical City Riyadh Saudi Arabia Department of Dentistry King Fahad Medical City Riyadh Saudi Arabia

The main role of this article is to describe dental assistants and the dental department’s role in the dental delivery system for Special health care needs (SCHN) by creating a structure to educate the dental assisting profession and project factors that have a significant impact on the dental assistant. The dental assisting management of SCHN patient’s profession including dental Assistance general responsibilities, regulation credentialing, and education. The SCHN patient’s management creates a challenge in all area of the dental department. Handling patient with a SCHN is underexplored throughout the dental staff especially when there is not enough theoretical foundation, education and training to deal with this category of patients. SCHN patients are defined as individuals who have abnormal behavioral impairments, mental conditions or/and chronic disease or abnormal laboratory results. Thus, the aim of this article is to guide all dental assistance staff in the best dental management choice for SCHN patients. all health care teams are part of patient care in most medical settings. A work environment supportive ensures positive outcomes for patient care. This article was considered as those categories of patients required more care and special way to deal with, moreover language, age, gender and education level of the patient are also considered significant parries. Not Many studies were found to support the care of SCHN patients in dentistry department. Taking experience from other area help to design a system to handle the SCHN even if it requires hiring a Dentist who is specialized in that filed.

关键词： Dental Management Dental Assistant Dentist Special Needs Special Health Care Need

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Form sentence to paragraph

Form sentence to paragraph

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作者： RobertG.bander

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