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A Secure and Efficient Information Authentication Scheme for E-Healthcare System

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Computers, Materials & Continua 2023年第9期76卷 3877-3896页

作者： Naveed Khan Jianbiao Zhang ghulam ali Mallah Shehzad Ashraf Chaudhry Faculty of Information Technology Beijing University of TechnologyBeijing100124China Department of Computer Science Shah Abdul Latif UniversityKhairpur66111Pakistan Department of Computer Engineering Faculty of Engineering ArchitectureNisantasi UniversityIstanbul34398Turkey

The mobile cellular network provides internet connectivity for heterogeneous Internet of Things(IoT)*** cellular network consists of several towers installed at appropriate locations within a smart *** cellular towers can be utilized for various tasks,such as e-healthcare systems,smart city surveillance,traffic monitoring,infrastructure surveillance,or sidewalk *** is a primary concern in data broadcasting,particularly authentication,because the strength of a cellular network’s signal is much higher frequency than the associated one,and their frequencies can sometimes be aligned,posing a significant *** a result,that requires attention,and without information authentication,such a barrier cannot be ***,we design a secure and efficient information authentication scheme for IoT-enabled devices tomitigate the flaws in the e-healthcare *** proposed protocol security shall check formally using the Real-or-Random(ROR)model,simulated using ProVerif2.03,and informally using pragmatic *** comparison,the performance phenomenon shall tackle by the already result available in the MIRACL cryptographic lab.

关键词： IoT-enable device e-healthcare authentication edge computing

Decision Support System for Diagnosis of Irregular Fovea

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Computers, Materials & Continua 2022年第6期71卷 5343-5353页

作者： ghulam ali Mallah Jamil Ahmed Muhammad Irshad Nazeer Mazhar ali Dootio Hidayatullah Shaikh Aadil Jameel Shah Abdul Latif University Khairpur77150Pakistan Sukkur IBA University Sukkur7720Pakistan Shaheed Benazir University Layari Karachi77202Pakistan

Detection of abnormalities in human eye is one of the wellestablished research areas of Machine *** Learning techniques are widely used for the diagnosis of RetinalDiseases(RD).Fovea is one of the significant parts of retina which would be prevented before the involvement of Perforated Blood Vessels(PBV).Retinopathy Images(RI)contains sufficient information to classify structural changes incurred upon PBV but Macular Features(MF)and Fovea Features(FF)are very difficult to detect because features ofMFand FF could be found with Similar Color Movements(SCM)with minor *** paper presents novel method for the diagnosis of Irregular Fovea(IF)to assist the doctors in diagnosis of irregular *** considering all above problems this paper proposes a three-layer decision support system to explore the hindsight knowledge of RI and to solve the classification problem of *** first layer involves data preparation,the second layer builds the decision model to extract the hidden patterns of fundus images by using Deep Belief Neural Network(DBN)and the third layer visualizes the results by using confusion *** paper contributes a data preparation algorithm for irregular fovea and a highest estimated classification accuracy measured about 96.90%.

关键词： Machine learning deep belief neural network eye disease fovea

Real-Time Multiple Guava Leaf Disease Detection from a Single Leaf Using Hybrid Deep Learning Technique

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Computers, Materials & Continua 2023年第1期74卷 1235-1257页

作者： Javed Rashid Imran Khan ghulam ali Shafiq ur Rehman Fahad Alturise Tamim Alkhalifah Department of CS&SE Islamic International UniversityIslamabad44000Pakistan Department of IT Services University of OkaraOkara56310Pakistan Department of CS University of OkaraOkara56310Pakistan Department of Botany University of OkaraOkara56310Pakistan Department of Computer College of Science and Arts in Ar RassQassim UniversityAr RassQassim52571Saudi Arabia

The guava plant has achieved viable significance in subtropics and tropics owing to its flexibility to climatic environments,soil conditions and higher human *** is cultivated in vast areas of Asian and Non-Asian countries,including *** guava plant is vulnerable to diseases,specifically the leaves and fruit,which result in massive crop and profitability *** existing plant leaf disease detection techniques can detect only one disease from a ***,a single leaf may contain symptoms of multiple *** study has proposed a hybrid deep learning-based framework for the real-time detection of multiple diseases from a single guava leaf in several ***,Guava Infected Patches Modified MobileNetV2 and U-Net(GIP-MU-NET)has been proposed to segment the infected guava *** proposed model consists of modified MobileNetv2 as an encoder,and the U-Net model’s up-sampling layers are used as a decoder ***,the Guava Leaf SegmentationModel(GLSM)is proposed to segment the healthy and infected *** the final step,the Guava Multiple Leaf Diseases Detection(GMLDD)model based on the YOLOv5 model detects various diseases from a guava *** self-collected datasets(the Guava Patches Dataset and the Guava Leaf Diseases Dataset)are used for training and *** proposed method detected the various defects,including five distinct classes,i.e.,anthracnose,insect attack,nutrition deficiency,wilt,and *** average,the GIP-MU-Net model achieved 92.41%accuracy,the GLSM gained 83.40%accuracy,whereas the proposed GMLDD technique achieved 73.3%precision,73.1%recall,71.0%mAP@0.5 and 50.3 mAP@0.5:0.95 scores for all the aforesaid classes.

关键词： Guava leaf diseases guava leaf segmentation guava patches segmentation multiple leaf diseases guava leaf diseases dataset

A Machine Learning-Based Attack Detection and Prevention System in Vehicular Named Data Networking

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Computers, Materials & Continua 2023年第11期77卷 1445-1465页

作者： Arif Hussain Magsi ali ghulam Saifullah Memon Khalid Javeed Musaed Alhussein Imad Rida State Key Laboratory of Networking and Switching Technology Beijing University of Post and TelecommunicationBeijing100876China Information Technology Center Sindh Agriculture UniversityTandojam70050Pakistan Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirate Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Laboratory Biomechanics and Bioengineering University of Technology of CompiegneCompiegne60200France

Named Data Networking(NDN)is gaining a significant attention in Vehicular Ad-hoc Networks(VANET)due to its in-network content caching,name-based routing,and mobility-supporting ***,existing NDN faces three significant challenges,including security,privacy,and *** particular,security attacks,such as Content Poisoning Attacks(CPA),can jeopardize legitimate vehicles with malicious *** instance,attacker host vehicles can serve consumers with invalid information,which has dire consequences,including road *** such a situation,trust in the content-providing vehicles brings a new *** the other hand,ensuring privacy and preventing unauthorized access in vehicular(VNDN)is another ***,NDN’s pull-based content retrieval mechanism is inefficient for delivering emergency messages in *** this connection,our contribution is *** existing rule-based reputation evaluation,we propose a Machine Learning(ML)-based reputation evaluation mechanism that identifies CPA attackers and legitimate *** on ML evaluation results,vehicles accept or discard served ***,we exploit a decentralized blockchain system to ensure vehicles’privacy by maintaining their information in a secure digital ***,we improve the default routing mechanism of VNDN from pull to a push-based content dissemination using Publish-Subscribe(Pub-Sub)*** implemented and evaluated our ML-based classification model on a publicly accessible BurST-Asutralian dataset for Misbehavior Detection(BurST-ADMA).We used five(05)hybrid ML classifiers,including Logistic Regression,Decision Tree,K-Nearest Neighbors,Random Forest,and Gaussian Naive *** qualitative results indicate that Random Forest has achieved the highest average accuracy rate of 100%.Our proposed research offers the most accurate solution to detect CPA in VNDN for safe,secure,and reliable vehicle communication.

关键词： Named data networking vehicular networks reputation caching machine-learning

Investigation of the sodium storage mechanism of iron fluoride hydrate cathodes using X-ray absorption spectroscopy and mossbauer spectroscopy

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Journal of Energy Chemistry 2023年第2期77卷 535-542,I0014页

作者： ghulam ali Muhammad Akbar Faiza Jan Iftikhar Qamar Wali Beata Kalska Szostko Dariusz Satuła Kyung Yoon Chung Energy Storage Research Center Korea Institute of Science and TechnologyHwarang-ro 14 gil 5Seongbuk-guSeoul 02792South Korea USPCAS-E National University of Sciences and Technology(NUST)H-12Islamabad 44000Pakistan Division of Energy&Environment Technology KIST SchoolKorea University of Science and Technology(UST)Hwarang-ro 14-gil-5Seongbuk-guSeoul 02792South Korea NUTECH School of Applied Sciences and Humanities National University of TechnologyIslamabad 44000Pakistan University of Białystok Faculty of ChemistryCiołkowskiego 1K15-424 BiałystokPoland University of Białystok Faculty of PhysicsCiołkowskiego 1L15-424 BiałystokPoland

Elucidation of a reaction mechanism is the most critical aspect for designing electrodes for highperformance secondary ***,we investigate the sodium insertion/extraction into an iron fluoride hydrate(FeF_(3)·0.5H_(2)O)electrode for sodium-ion batteries(SIBs).The electrode material is prepared by employing an ionic liquid 1-butyl-3-methylimidazolium-tetrafluoroborate,which serves as a reaction medium and precursor for F^(-)*** crystal structure of FeF_(3)·0.5H_(2)O is observed as pyrochlore type with large open 3-D tunnels and a unit cell volume of 1129A^(3).The morphology of FeF_(3)·0.5H_(2)O is spherical shape with a mesoporous *** microstructure analysis reveals primary particle size of around 10 *** FeF_(3)·0.5H_(2)O cathode exhibits stable discharge capacities of 158,210,and 284 mA h g^(-1) in three different potential ranges of 1.5-4.5,1.2-4.5,and 1.0-4.5 V,respectively at 0.05 C *** specific capacities remained stable in over 50 cycles in all three potential ranges,while the rate capability was best in the potential range of 1.5-4.5 *** electrochemical sodium storage mechanism is studied using X-ray absorption spectroscopy,indicating higher conversion at a more discharged ***-situ M?ssbauer spectroscopy strengthens the results for reversible reduction/oxidation of *** results will be favorable to establish high-performance cathode materials with selective voltage window for SIBs.

关键词： Iron fluoride Sodium-ion batteries Pyrochlore X-ray absorption spectroscopy Mössbauer spectroscopy

Deep Learning Method to Detect the Road Cracks and Potholes for Smart Cities

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Computers, Materials & Continua 2023年第4期75卷 1863-1881页

作者： Hong-Hu Chu Muhammad Rizwan Saeed Javed Rashid Muhammad Tahir Mehmood Israr Ahmad Rao Sohail Iqbal ghulam ali College of Civil Engineering Hunan UniversityChangsha410082China Department of CS University of OkaraOkara56310Pakistan Department of CS&SE Islamic International UniversityIslamabad44000Pakistan Department of IT Services University of OkaraOkara56310Pakistan Department of CS Government College UniversityFaisalabad38000Pakistan Department of Automation Science Beihang UniversityBeijing100191China

The increasing global population at a rapid pace makes road trafficdense;managing such massive traffic is challenging. In developing countrieslike Pakistan, road traffic accidents (RTA) have the highest mortality percentageamong other Asian countries. The main reasons for RTAs are roadcracks and potholes. Understanding the need for an automated system forthe detection of cracks and potholes, this study proposes a decision supportsystem (DSS) for an autonomous road information system for smart citydevelopment with the use of deep learning. The proposed DSS works in layerswhere initially the image of roads is captured and coordinates attached to theimage with the help of global positioning system (GPS), communicated tothe decision layer to find about the cracks and potholes in the roads, andeventually, that information is passed to the road management informationsystem, which gives information to drivers and the maintenance *** the decision layer, we projected a CNN-based model for pothole crackdetection (PCD). Aimed at training, a K-fold cross-validation strategy wasused where the value of K was set to 10. The training of PCD was completedwith a self-collected dataset consisting of 6000 images from Pakistani *** proposed PCD achieved 98% of precision, 97% recall, and accuracy whiletesting on unseen images. The results produced by our model are higher thanthe existing model in terms of performance and computational cost, whichproves its significance.

关键词： Road cracks and potholes CNN smart cities pothole crack detection decision support system

Use of Component Integration Services in Multidatabase Systems: A Feasible Solution for Integrating Academic Institutions or Commercial Industries

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Journal of Software Engineering and Applications 2023年第11期16卷 561-585页

作者： Mohammad ghulam ali Mohammad ghulam Murtuza Vinod Gupta School of Management Indian Institute of Technology Kharagpur Kharagpur India Research Service Center Post Graduate Department of Physics Tilka Manjhi Bhagalpur University Bhagalpur India

The book chapter is an extended version of the research paper entitled “Use of Component Integration Services in Multidatabase Systems”, which is presented and published by the 13th ISITA, the National Conference of Recent Trends in Mathematical and Computer Sciences, T.M.B. University, Bhagalpur, India, January 3-4, 2015. Information is widely distributed across many remote, distributed, and autonomous databases (local component databases) in heterogeneous formats. The integration of heterogeneous remote databases is a difficult task, and it has already been addressed by several projects to certain extents. In this chapter, we have discussed how to integrate heterogeneous distributed local relational databases because of their simplicity, excellent security, performance, power, flexibility, data independence, support for new hardware technologies, and spread across the globe. We have also discussed how to constitute a global conceptual schema in the multidatabase system using Sybase Adaptive Server Enterprise’s Component Integration Services (CIS) and OmniConnect. This is feasible for higher education institutions and commercial industries as well. Considering the higher educational institutions, the CIS will improve IT integration for educational institutions with their subsidiaries or with other institutions within the country and abroad in terms of educational management, teaching, learning, and research, including promoting international students’ academic integration, collaboration, and governance. This will prove an innovative strategy to support the modernization and large expansion of academic institutions. This will be considered IT-institutional alignment within a higher education context. This will also support achieving one of the sustainable development goals set by the United Nations: “Goal 4: ensure inclusive and quality education for all and promote lifelong learning”. However, the process of IT integration into higher educational institu

关键词： Relational Database Component Integration Services OmniConnect Multidatabase Global Conceptual Schema Distributed Database Local Conceptual Schema Database Integration IT Integration Higher Education Commercial Industries HEIs

Securing Cloud-Encrypted Data:Detecting Ransomware-as-a-Service(RaaS)Attacks through Deep Learning Ensemble

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Computers, Materials & Continua 2024年第4期79卷 857-873页

作者： Amardeep Singh Hamad ali Abosaq Saad Arif Zohaib Mushtaq Muhammad Irfan ghulam Abbas Arshad ali Alanoud Al Mazroa School of Computer Information Sciences University of CumberlandsWilliamsburgKentucky40769USA Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Electrical Engineering The University of LahoreLahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware *** study provides a new approach for RaaS attack detection which uses an ensemble of deep learning *** this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is *** the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are ***,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested *** proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%*** empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual *** expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.

关键词： Cloud encryption RaaS ensemble threat detection deep learning cybersecurity

Morphometry of leaf and shoot variables to assess aboveground biomass structure and carbon sequestration by different varieties of white mulberry(Morus alba L.)

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Journal of Forestry Research 2021年第6期32卷 2291-2300页

作者： ghulam ali Bajwa Muhammad Umair Yasir Nawab Zahid Rizwan Pakistan Forest Institute Peshawar 25130Pakistan National Textile University Faisalabad 37610Pakistan

Mulberry is economically important and can also play a pivotal role in mitigating greenhouse *** and shoot traits were measured for Morus alba ***,*** ***,*** ***,and *** ***-1 to assess aboveground biomass(AGB)and carbon ***-specific and multivariety allometric AGB models were developed using the equivalent diameter at breast height(EDBH)and plant height(H).The completeharvest method was used to measure leaf and shoot traits and biomass,and the ash method was used to measure organic carbon *** results showed significant(p<0.01)varietal differences in leaf and shoot traits,AGB and carbon ***-1 variety had the greatest leaf density(mean±SE:1828.3±0.3 leaves tree^(-1)),Karyansuban had the largest mean leaf area(185.94±8.95 cm^(2)).A diminishing return was found between leaf area and leaf *** had the highest shoot density per tree(46.6±1.83 shoots tree^(-1)),total shoot length(264.1±2.32 m),dry biomass(16.69±0.58 kg tree^(-1)),carbon sequestration(9.99±0.32 kg tree^(-1))and CO_(2) mitigation(36.67±1.16 kg).The variety-specific AGB models b(EDBH)and b(EDBH)2 showed good fit and reasonable accuracy with a coefficient of determination(R^(2))=0.98-0.99,standard error of estimates(SEE)=0.1125-0.3130 and root mean square error(RMSE)=*** multivariety models bln(EDBH)and(EDBH)0.756 showed good-fitness and accuracy with R^(2)=0.85-0.86,SEE=1.6231-1.6445 and RMSE=*** the basis of these findings,variety Latifolia has good potential for biomass production,and allometric equations based on EDBH can be used to estimate AGB with a reasonable accuracy.

关键词： Allometry Biomass estimation CO_(2)mitigation Moraceae Mulberry Regression models