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A Fused Machine Learning Approach for Intrusion Detection System

Computers, Materials & Continua 2023年第2期74卷 2607-2623页

作者： Muhammad Sajid Farooq Sagheer Abbas Atta-ur-Rahman kiran sultan Muhammad Adnan Khan Amir Mosavi School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam 31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Software Gachon UniversitySeongnam13120Korea John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of internet.The interconnectivity of networks has brought various complexities in maintaining network availability,consistency,and discretion.Machine learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit activities.An intrusion detection system controls the flow of network traffic with the help of computer systems.Various deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network traffic.For this purpose,when the network traffic encounters known or unknown intrusions in the network,a machine-learning framework is needed to identify and/or verify network intrusion.The Intrusion detection scheme empowered with a fused machine learning technique(IDS-FMLT)is proposed to detect intrusion in a heterogeneous network that consists of different source networks and to protect the network from malicious attacks.The proposed IDS-FMLT system model obtained 95.18%validation accuracy and a 4.82%miss rate in intrusion detection.

关键词： Fused machine learning heterogeneous network intrusion detection

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Automated File Labeling for Heterogeneous Files Organization Using Machine Learning

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Computers, Materials & Continua 2023年第2期74卷 3263-3278页

作者： Sagheer Abbas Syed Ali Raza MAKhan Muhammad Adnan Khan Atta-ur-Rahman kiran sultan Amir Mosavi School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Science GC University LahorePakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Software Pattern Recognition and Machine Learning LabGachon UniversitySeongnam13120Korea Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah31261Saudi Arabia John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

File labeling techniques have a long history in analyzing the anthological trends in computational linguistics.The situation becomes worse in the case of files downloaded into systems from the Internet.Currently,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user files.Currently,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic modeling.However,one major drawback of current topic modeling approaches is better results.They rely on specific language types and domain similarity of the data.In this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the files.The results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.

关键词： Automated file labeling file organization machine learning topic modeling

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Transmitter-Receiver Path Selection for Cell Range Extension Using Multi-Hop D2D

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Computers, Materials & Continua 2021年第8期68卷 2075-2093页

作者： Farah Akif kiran sultan Aqdas N.Malik Ijaz M.Qureshi Saba Mahmood Department of Electrical Engineering International Islamic UniversityIslamabad44000Pakistan Department of CIT FASKing Abdulaziz UniversityJeddah21551Saudi Arabia Department of Electrical Engineering Air UniversityIslamabad44000Pakistan Department of Computer Science Bahria UniversityIslamabad44000Pakistan

Conventional approach of dealing with more users per coverage area in cellular networks implies densifying the amount of(Access Point)AP which will eventually result in a larger carbon footprint.In this paper,we propose a base station off-loading and cell range extension(CRE)scheme based on multi-hop device-to-device(MHD2D)path selection between transmitter and receiver node.The paper also provides derivations of upper and lower bounds for energy efficiency,capacity,and transmit power.The proposed path selection scheme is inspired by the foraging behavior of honey bees.We present the algorithm as a modified variant of the artificial bee colony algorithm(MVABC).The proposed optimization problem is modeled as a minimization problem where we optimize the Energy Efficiency(EE).The proposed path selection MVABC is compared with the Genetic Algorithm(GA)and also with classical artificial bee colony(ABC)through simulations and statistical analysis.The student’s t-test,p-value,and standard error of means(SEM)clearly show that MVABC based path selection out-performs the GA and classical ABC schemes.MVABC based approach is 66%more efficient when compared with classic ABC and about 62%efficient when compared with GA based scheme.

关键词： Multi-hop ultra-dense D2D path-selection ABC GA

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Supervised Machine Learning-Based Prediction of COVID-19

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Computers, Materials & Continua 2021年第10期69卷 21-34页

作者： Atta-ur-Rahman kiran sultan Iftikhar Naseer Rizwan Majeed Dhiaa Musleh Mohammed Abdul Salam Gollapalli Sghaier Chabani Nehad Ibrahim Shahan Yamin Siddiqui Muhammad Adnan Khan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of Computer Information System College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of CIT Faculty of Applied StudiesKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science&Information Technology Superior UniversityLahore54000Pakistan Directorate of IT The Islamia University of BahawalpurBahawalpur63100Pakistan School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science Minhaj University LahoreLahore54000Pakistan Department of Computer Science Faculty of ComputingRiphah International University Lahore CampusLahore54000Pakistan

COVID-19 turned out to be an infectious and life-threatening viral disease,and its swift and overwhelming spread has become one of the greatest challenges for the world.As yet,no satisfactory vaccine or medication has been developed that could guarantee its mitigation,though several efforts and trials are underway.Countries around the globe are striving to overcome the COVID-19 spread and while they are finding out ways for early detection and timely treatment.In this regard,healthcare experts,researchers and scientists have delved into the investigation of existing as well as new technologies.The situation demands development of a clinical decision support system to equip the medical staff ways to timely detect this disease.The state-of-the-art research in Artificial intelligence(AI),Machine learning(ML)and cloud computing have encouraged healthcare experts to find effective detection schemes.This study aims to provide a comprehensive review of the role of AI&ML in investigating prediction techniques for the COVID-19.A mathematical model has been formulated to analyze and detect its potential threat.The proposed model is a cloud-based smart detection algorithm using support vector machine(CSDC-SVM)with cross-fold validation testing.The experimental results have achieved an accuracy of 98.4%with 15-fold cross-validation strategy.The comparison with similar state-of-the-art methods reveals that the proposed CSDC-SVM model possesses better accuracy and efficiency.

关键词： COVID-19 CSDC-SVM artificial intelligence machine learning cloud computing support vector machine

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Exploration of IoT Nodes Communication Using LoRaWAN in Forest Environment

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Computers, Materials & Continua 2022年第6期71卷 6239-6256页

作者： Anshul Sharma Divneet Singh Kapoor Anand Nayyar Basit Qureshi kiran Jot Singh Khushal Thakur Embedded Systems&Robotics Research Group Chandigarh UniversityMohali140413PunjabIndia Graduate School Duy Tan UniversityDa Nang550000Vietnam Faculty of Information Technology Duy Tan UniversityDa Nang550000Vietnam Department of Computer Science Prince Sultan UniversityRiyadh11586Saudi Arabia

The simultaneous advances in the Internet of Things(IoT),Artificial intelligence(AI)and Robotics is going to revolutionize our world in the near future.In recent years,LoRa(Long Range)wireless powered by LoRaWAN(LoRa Wide Area Network)protocol has attracted the attention of researchers for numerous applications in the IoT domain.LoRa is a low power,unlicensed Industrial,Scientific,and Medical(ISM)bandequipped wireless technology that utilizes a wide area network protocol,i.e.,LoRaWAN,to incorporate itself into the network infrastructure.In this paper,we have evaluated the LoRaWAN communication protocol for the implementation of the IoT(Internet of Things)nodes’communication in a forest scenario.The outdoor performance of LoRa wireless in LoRaWAN,i.e.,the physical layer,has been evaluated in the forest area of Kashirampur Uttarakhand,India.Hence,the present paper aims towards analyzing the performance level of the LoRaWAN technology by observing the changes in Signal to Noise Ratio(SNR),Packet Reception Ratio(PRR)and Received Signal Strength Indicator(RSSI),with respect to the distance between IoT nodes.The article focuses on estimating network lifetime for a specific set of LoRa configuration parameters,hardware selection and power constraints.From the experimental results,it has been observed that transmissions can propagate to a distance of 300 m in the forest environment,while consuming approx.63%less energy for spreading factor 7 at 2 dBm,without incurring significant packet loss with PRR greater than 80%.

关键词： LoRa LoRaWAN IoT communication protocol wireless sensor networks packet reception ratio

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Molecular diagnosis of 5α-reductase-2 gene mutation in two Indian families with male pseudohermaphroditism

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Asian Journal of Andrology 2008年第5期10卷 815-818页

作者： Marumudi Eunice Pascal Philibert Bindu Kulshreshtha Francoise Audran Francoise Paris Madan L. Khurana Praveen E. Pulikkanath kiran Kucheria Charles sultan Ariachery C. Ammin Department of Endocrinology and Metabolism All India Institute of Medical Sciences Ansari Nagar New Delhi-110029 India Department of Anatomy All India Institute of Medical Sciences Ansari Nagar New Delhi-110029 India Pediatric Endocrine Unit and the Hormones Laboratory of the University Hospital of Montpellier 34295 Montpellier Cedex 5 France

Aim： To identify the genotype of two Indians with male pseudohermaphroditism. Methods： Standard radioimmunoassay procedure was used for estimating hormonal levels. Conventional cytogenetic analysis was carded out for diagnosing the genetic sex in these subjects with genital ambiguity. Molecular analysis was carried out by standard polymerase chain reaction procedure using different sets of primers and reaction conditions specific for the 5α- reductase type 2 gene （SRDSA2） gene. Direct sequencing was carried out using the ABI Prism dye terminator sequencing kit and the ABI 310 sequencing apparatus. Results： We found an SRDSA2 gene mutation in exon 5, where arginine is substituted with glutamine （R246Q）, in two males with pseudohermaphroditism and ambiguous genitalia from unrelated families. This is the first time this mutation has been reported in individuals from India. Conclusion： Identification of the R246Q mutation of the SRDSA2 gene from two unrelated Indian families possibly extends the founder gene effect.

关键词： male pseudohermaphroditism 5αRD-2 deficiency dihydrotestosterone SRD5A2 gene mutation perineoscrotal hypospadias

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Analysis of Pneumonia Model via Efficient Computing Techniques

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Computers, Materials & Continua 2022年第3期70卷 6073-6088页

作者： Kamaledin Abodayeh Ali Raza Muhammad Rafiq Muhammad Shoaib Arif Muhammad Naveed Zunir Zeb Syed Zaheer Abbas kiran Shahzadi Sana Sarwar Qasim Naveed Badar Ul Zaman Muhammad Mohsin Department of Mathematics and General Sciences Prince Sultan University Riyadh66833Saudi Arabia Department of Mathematics Govt.Maulana Zafar Ali Khan Graduate College Wazirabad52000Punjab Higher Education Department(PHED)Lahore54000Pakistan Department of Mathematics National College of Business Administration and Economics Lahore54660Pakistan Department of Mathematics Faculty of SciencesUniversity of Central PunjabLahore54500Pakistan Department of Mathematics Air UniversityIslamabad44000Pakistan Department of Mathematics Technische Universitat Chemnitz6209111Germany

Pneumonia is a highly transmissible disease in children.According to the World Health Organization(WHO),the most affected regions include south Asia and sub-Saharan Africa.Worldwide,15%of pediatric deaths can be attributed to pneumonia.Computing techniques have a significant role in science,engineering,and many other fields.In this study,we focused on the efficiency of numerical techniques via computer programs.We studied the dynamics of the pneumonia-like infections of epidemic models using numerical techniques.We discuss two types of analysis:dynamical and numerical.The dynamical analysis included positivity,boundedness,local stability,reproduction number,and equilibria of the model.We also discusswell-known computing techniques including Euler,Runge Kutta,and non-standard finite difference(NSFD)for the model.The non-standard finite difference(NSFD)technique shows convergence to the true equilibrium points of the model for any time step size.However,Euler and Runge Kutta do not work well over large time intervals.Computing techniques are the suitable tool for crosschecking the theoretical analysis of the model.

关键词： Pneumonia disease epidemic model computing techniques convergence analysis

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Pedigree and SSR Data Analysis Reveal Dominant Prevalence of Few Parents in Pedigrees of Pakistani Wheat Varieties

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American Journal of Molecular Biology 2015年第1期5卷 1-6页

作者： Muhammad Sajjad sultan Habibullah Khan Rizwana Maqbool Department of Environmental Sciences COMSATS Institute of Information Technology Vehari Pakistan Center for Agricultural Biochemistry and Biotechnology University of Agriculture Faisalabad Pakistan Department of Crop and Soil Sciences Washington State University Pullman USA

The international recognition of the importance of genetic diversity demands continuous estimation of genetic diversity of in hand population as test of its buffering capacity against all putative threats. Randomly selected Pakistani wheat varieties developed during 1965-1999 and 2000-2011 were evaluated on the basis of pedigree and SSR data. At 2nd and 3rd levels of pedigree, average occurrence of a parent per variety was 2.1 times. The dominating parents included BLUEBIRD, KALYANSONA and SIETE-CERROS-66, which were present in the pedigrees of 71.42%, 64.28%, and 58.57% varieties, respectively. The varieties INQLAB-91 and kiran-95 had the same pedigree and were genetically identical as revealed by SSR data. Similarly, varieties PAVON-76 and SOGHAT-90 also had the same parents in their pedigrees. This genetic similarity was also confirmed by SSR based cluster. The SSR based PC1 and PC2 showed narrow genetic diversity confirming the presence of few dominating parents. The results emphasize the inclusion of novel and genetically diverse parents in Pakistani wheat breeding programs to maintain broader genetic base of varieties/cultivars for buffering the effects of ever changing virulent pathogens and crop growth environments.

关键词： Genetic Diversity Pedigrees SSR Wheat

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