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Anomaly-Based Intrusion Detectionmodel Using Deep Learning for IoT Networks

Computer modeling in Engineering & Sciences 2024年第10期141卷 823-845页

作者： muaadh A.alsoufi maheyzah md Siraj Fuad A.ghaleb muna al-Razgan mahfoudh Saeed al-Asaly Taha alfakih Faisal Saeed Faculty of Computing Universiti Teknologi Malaysia(UTM)Johor Bahru81310Malaysia DAAI Research group College of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11345Saudi Arabia

The rapid growth of Internet of Things(IoT)devices has brought numerous benefits to the interconnected ***,the ubiquitous nature of IoT networks exposes them to various security threats,including anomaly intrusion *** addition,IoT devices generate a high volume of unstructured *** intrusion detection systems often struggle to cope with the unique characteristics of IoT networks,such as resource constraints and heterogeneous data *** the unpredictable nature of network technologies and diverse intrusion methods,conventional machine-learning approaches seem to lack *** numerous research domains,deep learning techniques have demonstrated their capability to precisely detect *** study designs and enhances a novel anomaly-based intrusion detection system(AIDS)for IoT ***,a Sparse Autoencoder(SAE)is applied to reduce the high dimension and get a significant data representation by calculating the reconstructed ***,the Convolutional Neural Network(CNN)technique is employed to create a binary classification *** proposed SAE-CNN approach is validated using the Bot-IoT *** proposed models exceed the performance of the existing deep learning approach in the literature with an accuracy of 99.9%,precision of 99.9%,recall of 100%,F1 of 99.9%,False Positive Rate(FPR)of 0.0003,and True Positive Rate(TPR)of *** addition,alternative metrics,such as training and testing durations,indicated that SAE-CNN performs better.

关键词： IoT anomaly intrusion detection deep learning sparse autoencoder convolutional neural network

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Image Splicing Forgery Detection Using Feature-Based of Sonine Functions and Deep Features

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Computers, materials & Continua 2024年第1期78卷 795-810页

作者： ala’a R.al-Shamasneh Rabha W.Ibrahim Department of Computer Science College of Computer&Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Science and mathematics Lebanese American UniversityBeirut11022801Lebanon Department of mathematics Mathematics Research CenterNear East UniversityNicosia99138Turkey Information and Communication Technology Research group Scientific Research CenterAlayen UniversityDhi Qar64001Iraq

The growing prevalence of fake images on the Internet and social media makes image integrity verification a crucial research *** of the most popular methods for manipulating digital images is image splicing,which involves copying a specific area from one image and pasting it into *** were made to mitigate the effects of image splicing,which continues to be a significant research *** study proposes a new splicing detectionmodel,combining Sonine functions-derived convex-based features and deep *** stages make up the proposed *** first step entails feature extraction,then classification using the“support vector machine”(SVm)to differentiate authentic and spliced *** proposed Sonine functions-based feature extraction model reveals the spliced texture details by extracting some clues about the probability of image *** proposed model achieved an accuracy of 98.93% when tested with the CASIA V2.0 dataset“Chinese Academy of Sciences,Institute of Automation”which is a publicly available dataset for forgery *** experimental results show that,for image splicing forgery detection,the proposed Sonine functions-derived convex-based features and deep features outperform state-of-the-art techniques in terms of accuracy,precision,and ***,the obtained detection accuracy attests to the benefit of using the Sonine functions alongside deep feature *** the regions or locations where image tampering has taken place is limited by the *** research will need to look into advanced image analysis techniques that can offer a higher degree of accuracy in identifying and localizing tampering regions.

关键词： Image forgery image splicing deep learning Sonine functions

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Automatic Rule Discovery for Data Transformation Using Fusion of Diversified Feature Formats

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Computers, materials & Continua 2024年第7期80卷 695-713页

作者： g.Sunil Santhosh Kumar m.Rudra Kumar Department of CSE Jawaharlal Nehru Technological UniversityAnantapur515002India Department of CSE Marri Laxman Reddy Institute of Technology and ManagementHyderabad500043India Department of Information Technology Mahatma Gandhi Institute of TechnologyHyderabad500075India

This article presents an innovative approach to automatic rule discovery for data transformation tasks leveraging XgBoost,a machine learning algorithm renowned for its efficiency and *** framework proposed herein utilizes the fusion of diversified feature formats,specifically,metadata,textual,and pattern *** goal is to enhance the system’s ability to discern and generalize transformation rules fromsource to destination formats in varied ***,the article delves into the methodology for extracting these distinct features from raw data and the pre-processing steps undertaken to prepare the data for the *** sections expound on the mechanism of feature optimization using Recursive Feature Elimination(RFE)with linear regression,aiming to retain the most contributive features and eliminate redundant or less significant *** core of the research revolves around the deployment of the XgBoostmodel for training,using the prepared and optimized feature *** article presents a detailed overview of the mathematical model and algorithmic steps behind this ***,the process of rule discovery(prediction phase)by the trained XgBoost model is explained,underscoring its role in real-time,automated data *** employingmachine learning and particularly,the XgBoost model in the context of Business Rule Engine(BRE)data transformation,the article underscores a paradigm shift towardsmore scalable,efficient,and less human-dependent data transformation *** research opens doors for further exploration into automated rule discovery systems and their applications in various sectors.

关键词： XgBoost business rule engine machine learning categorical query language humanitarian computing environment

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Customized Convolutional Neural Network for Accurate Detection of Deep Fake Images in Video Collections

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Computers, materials & Continua 2024年第5期79卷 1995-2014页

作者： Dmitry gura Bo Dong Duaa mehiar Nidal al Said Department of Cadastre and geoengineering Kuban State Technological UniversityKrasnodar350072Russian Federation Department of geodesy Kuban State Agrarian UniversityKrasnodar350072Russian Federation School of Innovation and Entrepreneurship Liaoning UniversityLiaoning110031China Department of IT Middle East UniversityAmman11831Jordan College of mass Communication Ajman UniversityP.O Box 346AjmanUnited Arab Emirates

The motivation for this study is that the quality of deep fakes is constantly improving,which leads to the need to develop new methods for their *** proposed Customized Convolutional Neural Network method involves extracting structured data from video frames using facial landmark detection,which is then used as input to the *** customized Convolutional Neural Network method is the date augmented-based CNN model to generate‘fake data’or‘fake images’.This study was carried out using Python and its *** used 242 films from the dataset gathered by the Deep Fake Detection Challenge,of which 199 were made up and the remaining 53 were *** seconds were allotted for each *** were 318 videos used in all,199 of which were fake and 119 of which were *** proposedmethod achieved a testing accuracy of 91.47%,loss of 0.342,and AUC score of 0.92,outperforming two alternative approaches,CNN and ***,our method succeeded in greater accuracy than contemporary models such as XceptionNet,meso-4,EfficientNet-BO,mesoInception-4,Vgg-16,and *** novelty of this investigation is the development of a new Convolutional Neural Network(CNN)learning model that can accurately detect deep fake face photos.

关键词： Deep fake detection video analysis convolutional neural network machine learning video dataset collection facial landmark prediction accuracy models

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A regular mOg black hole's impact on shadows and gravitational weak lensing in the presence of a quintessence field

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Communications in Theoretical Physics 2024年第8期76卷 93-104页

作者： Ahmad al-Badawi Sanjar Shaymatov mirzabek alloqulov Anzhong Wang Department of Physics Al-Hussein Bin Talal University Institute for Theoretical Physics and Cosmology Zhejiang University of Technology Tashkent State Technical University University of Tashkent for Applied Sciences New Uzbekistan University Institute of Fundamental and Applied Research National Research University TIIAME gCAP-CASPER Physics Department Baylor University

We investigate the impact of the modified gravity（mOg） field and the quintessence scalar field on horizon evolution, black hole（BH） shadow and the weak gravitational lensing around a static spherically symmetric BH. We first begin to write the BH metric associated with the mOg parameter and quintessence scalar field. We then determine the BH shadow and obtain numerical solutions for the photon sphere and shadow radius. We show that the mOg（α） and the quintessence（c） parameters have a significant impact on the BH shadow and photon *** on the analysis, we further show that the combined effects of the mOg parameter and quintessence field can increase the values of BH shadow and photon sphere radii. We also obtain constraints on the BH parameters by applying the observational data of Sgr A★and m87★.Finally, we consider the weak deflection angle of BH within the context of the gauss–Bonnet theorem（gBT） and show that the combined effects of the mOg and quintessence parameters do make the value of the deflection angle increase, and find this remarkable property is in good agreement with the physical meaning of both parameters that can maintain the strong gravitational field in the surrounding environment of a BH.

关键词： gravitational weak lensing modified gravity quintessence field shadows

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Influence of curing conditions on the shrinkage behavior of three-dimensional printed concrete formwork

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Frontiers of Structural and Civil Engineering 2024年第8期18卷 1225-1236页

作者： m.BEKAERT K.van TITTELBOOm g.de SCHUTTER magnel-Vandepitte Laboratory for structural Engineering and Building materials Department of Structural Engineering and Building MaterialsFaculty of Engineering and ArchitectureGhent UniversityGhent 60 B-9052Belgium

The use of three-dimensional(3D)printed concrete as formwork is becoming more widely applied within the ***,the technology is still not optimized and there are many reports of preliminary cracking during the curing of cast *** is believed to result from differential shrinkage between the printed and cast *** cracks(in the printed concrete or at the interface between the infill and printed concrete)form a preferential path for aggressive substances and can reduce the durability of the combined concrete *** ensure the desired service life of the structure,it is important that the differential shrinkage between cast and printed concrete is *** study investigated the effect of curing conditions on the differential shrinkage behavior of 3D and cast *** influence of prewetting of the dry-cured 3D printed formwork was also *** the experimental program,a vibrated and self-compacting concrete were used as cast *** 3D printed formwork was produced and combined with cast concrete to simulate a concrete *** formwork was cured for 1,7,or 28 d exposed to the air(relative humidity:60%or 95%)or submerged in *** length change of the combined elements was observed over 56 d after concrete casting and throughout the thickness of the *** show that increasing the curing period in dry conditions of the printed concrete leads to an expansion of the formwork on the first day after *** expansion leads to a non-uniform strain evolution throughout the curing period of the combined *** concrete formwork stored in wet conditions does not expand after the casting process but tends to show a decreasing linear deformation within the whole elements.

关键词： 3D concrete printing formwork shrinkage curing

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Kaposi Sarcoma after Kidney Transplant: A Clinical Case Report

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Open Journal of Nephrology 2024年第1期14卷 115-123页

作者： meryem Benbella Zaineb Kaouiri Imane saidi Naima Ouzedoun Tarik Bouattar Department of Nephrology-Dialysis-Renal Transplantation Ibn Sina University Hospital in Rabat Rabat Morocco Faculty of medicine and Pharmacy in Rabat Mohammed V University Rabat Morocco

Kaposi sarcoma is a neoplasm caused by human herpesvirus 8 (HHV8) that most commonly affects immunosuppressed patients. The skin is the most affected area, but other sites can be involved such as the lung, digestive tract and lymph nodes. The classical presentation involves a violaceous skin lesion that can be small or hidden, leading to a delay in diagnosis. We report a clinical case of a kidney transplant patient, who presented, 14 months after kidney transplant, with unilateral edema of the inferior member and cutaneous rash misdiagnosed and taken initially for erysipelas. The diagnosis of Kaposi’s sarcoma was retained, on a lymph node biopsy of an inguinal adenopathy. The evolution was marked by a local and general improvement after systemic chemotherapy, reducing Tacrolimus and discontinuation of mycophenolate mofetil. graft function remained stable during the follow-up.

关键词： Kaposi Kidney Transplant HHV8 Immunosuppression

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The Protective Effect of moringa oleifera Leaves Extract on Paracetamol Hepatotoxicity in male Rats

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Journal of Biomedical Science and Engineering 2024年第3期17卷 72-82页

作者： Reham m. al-Sultan Noorah Saleh al-Sowayan Department of Biology College of Science Qassim University Buraydah Saudi Arabia

In recent years, there has been an increase in concern regarding the effects of paracetamol poisoning on liver tissues, particularly when consumed in large amounts. Some studies have estimated that paracetamol is involved in 56% of acute liver diseases, whereas 0.4% of paracetamol overdose cases result in fatal-ity. In this study, the effects of moringa oleifera on paracetamol toxicity in the liver were explored. It has been demonstrated that moringa oleifera is highly nu-tritious, contains bioactive molecules, and is therapeutically beneficial. many studies have shown that moringa oleifera leaves possess a wide range of biologi-cal properties, including antioxidant, tissue protection, analgesic, antihyperten-sive, and immunomodulatory activities. This study highlights the protective role of moringa oleifera on handling possible paracetamol hepatotoxicity in male rats. .

关键词： moringa oleifera Paracetamol Hepatotoxicity Oxidative Stress

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Semi-analytical investigation of heat transfer in a porous convective radiative moving longitudinal fin exposed to magnetic field in the presence of a shape-dependent trihybrid nanofluid

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Applied mathematics and mechanics(English Edition) 2024年第1期45卷 197-216页

作者： C.g.PAVITHRA B.J.gIREESHA m.L.KEERTHI Department of Pg Studies and Research in mathematics Kuvempu UniversityShankaraghatta 577451India Department of mathematics and Statistics M.S.Ramaiah University of Applied SciencesBengaluru 560058India

The thermal examination of a non-integer-ordered mobile fin with a magnetism in the presence of a trihybrid nanofluid(Fe_3O_4-Au-Zn-blood) is carried out. Three types of nanoparticles, each having a different shape, are considered. These shapes include spherical(Fe_3O_4), cylindrical(Au), and platelet(Zn) configurations. The combination approach is utilized to evaluate the physical and thermal characteristics of the trihybrid and hybrid nanofluids, excluding the thermal conductivity and dynamic viscosity. These two properties are inferred by means of the interpolation method based on the volume fraction of nanoparticles. The governing equation is transformed into a dimensionless form, and the Adomian decomposition Sumudu transform method(ADSTm) is adopted to solve the conundrum of a moving fin immersed in a trihybrid nanofluid. The obtained results agree well with those numerical simulation results, indicating that this research is reliable. The influence of diverse factors on the thermal overview for varying noninteger values of γ is analyzed and presented in graphical representations. Furthermore, the fluctuations in the heat transfer concerning the pertinent parameters are studied. The results show that the heat flux in the presence of the combination of spherical, cylindrical, and platelet nanoparticles is higher than that in the presence of the combination of only spherical and cylindrical nanoparticles. The temperature at the fin tip increases by 0.705 759% when the value of the Peclet number increases by 400%, while decreases by 11.825 13% when the value of the Hartman number increases by 400%.

关键词： convection radiation moving longitudinal fin Adomian decomposition Sumudu transform method(ADSTm) trihybrid nanofluid magnetic field

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

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

作者： Widad Elbakri maheyzah md.Siraj Bander ali Saleh al-rimy 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 *** security 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 security *** 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 security 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 security 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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