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Multi-dimensional information-driven many-objective software remodularization approach

Frontiers of computer Science 2023年第3期17卷 45-62页

作者： Amarjeet PRAJAPATI Anshu PARASHAR Amit RATHEE department of computer Science engineering&information technology Jaypee Istitute of Information TechnologyNoida 201307India department of computer Science&engineering Thapar Institute of Engineering&TechnologyPunjab 147004India department of computer Science Government College BarotaHaryana 131301India

Most of the search-based software remodularization(SBSR)approaches designed to address the software remodularization problem(SRP)areutilizing only structural information-based coupling and cohesion quality criteria.However,in practice apart from these quality criteria,there require other aspects of coupling and cohesion quality criteria such as lexical and changed-history in designing the modules of the software systems.Therefore,consideration of limited aspects of software information in the SBSR may generate a sub-optimal modularization solution.Additionally,such modularization can be good from the quality metrics perspective but may not be acceptable to the developers.To produce a remodularization solution acceptable from both quality metrics and developers’perspectives,this paper exploited more dimensions of software information to define the quality criteria as modularization objectives.Further,these objectives are simultaneously optimized using a tailored manyobjective artificial bee colony(MaABC)to produce a remodularization solution.To assess the effectiveness of the proposed approach,we applied it over five software projects.The obtained remodularization solutions are evaluated with the software quality metrics and developers view of remodularization.Results demonstrate that the proposed software remodularization is an effective approach for generating good quality modularization solutions.

关键词： software restructuring remodularization multiobjective optimization software coupling and cohesion

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A Novel Energy and Communication Aware Scheduling on Green Cloud Computing

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computers, Materials & Continua 2023年第12期77卷 2791-2811页

作者： Laila Almutairi Shabnam Mohamed Aslam department of computer engineering Computer Science and Information Technology CollegeMajmaah UniversityAl Majmaah11952Saudi Arabia department of information technology Computer Science and Information Technology CollegeMajmaah UniversityAl Majmaah11952Saudi Arabia

The rapid growth of service-oriented and cloud computing has created large-scale data centres worldwide.Modern data centres’operating costs mostly come from back-end cloud infrastructure and energy consumption.In cloud computing,extensive communication resources are required.Moreover,cloud applications require more bandwidth to transfer large amounts of data to satisfy end-user requirements.It is also essential that no communication source can cause congestion or bag loss owing to unnecessary switching buffers.This paper proposes a novel Energy and Communication(EC)aware scheduling(EC-scheduler)algorithm for green cloud computing,which optimizes data centre energy consumption and traffic load.The primary goal of the proposed EC-scheduler is to assign user applications to cloud data centre resources with minimal utilization of data centres.We first introduce a Multi-Objective Leader Salp Swarm(MLSS)algorithm for task sorting,which ensures traffic load balancing,and then an Emotional Artificial Neural Network(EANN)for efficient resource allocation.EC-scheduler schedules cloud user requirements to the cloud server by optimizing both energy and communication delay,which supports the lower emission of carbon dioxide by the cloud server system,enabling a green,unalloyed environment.We tested the proposed plan and existing cloud scheduling methods using the GreenCloud simulator to analyze the efficiency of optimizing data centre energy and other scheduler metrics.The EC-scheduler parameters Power Usage Effectiveness(PUE),Data Centre Energy Productivity(DCEP),Throughput,Average Execution Time(AET),Energy Consumption,and Makespan showed up to 26.738%,37.59%,50%,4.34%,34.2%,and 33.54%higher efficiency,respectively,than existing state of the art schedulers concerning number of user applications and number of user requests.

关键词： EC-scheduler green cloud energy efficiency task scheduling task sorting resource allocation

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Time and energy efficient data collection via UAV

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Science China(information Sciences) 2022年第8期65卷 182-196页

作者： Tianhao WANG Xiaowei PANG Jie TANG Nan ZHAO Xiuyin ZHANG Xianbin WANG School of information and Communication engineering Dalian University of Technology department of Electrical and computer engineering Western University School of Electronic and information engineering South China University of Technology

Using unmanned aerial vehicles(UAVs) for data collection has emerged as a promising technique to achieve both time-and energy-efficient data gathering while keeping data fresh. In this study, two schemes are proposed for flight cycle minimization and energy efficiency maximization to collect data from ground sensors. We first minimize the flight cycle by jointly optimizing the wake-up scheduling of sensors, the trajectory,and the time slot, which is a mixed-integer non-convex problem and difficult to solve directly. To this end,we propose an iterative algorithm based on block coordinate descent and successive convex approximation to decouple the original non-convex problem into two sub-problems and the constraints are turned to be convex approximately. Furthermore, the energy efficiency is maximized since the limited energy is a critical issue in UAV communication systems. We approximate the two subproblems as convex optimizations by introducing slack variables and applying SCA. The approximate energy efficiency is a fractional expression, and we use Dinkelbach’s method to solve it. Numerical results show that the flight cycle is minimized in the first scheme with the data requirement satisfied, while in the second scheme, the energy efficiency is maximized with the trade-off between the transmission data and the propulsion power consumption.

关键词： data collection energy efficiency maximization time minimization trajectory optimization unmanned aerial vehicle (UAV)

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Feature selection techniques for microarray datasets:a comprehensive review,taxonomy,and future directions

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Frontiers of information technology & Electronic engineering 2022年第10期23卷 1451-1478页

作者： Kulanthaivel BALAKRISHNAN Ramasamy DHANALAKSHMI department of computer Science and engineering Indian Institute of Information TechnologyTiruchirappalli 620012India

For optimal results,retrieving a relevant feature from a microarray dataset has become a hot topic for researchers involved in the study of feature selection(FS)techniques.The aim of this review is to provide a thorough description of various,recent FS techniques.This review also focuses on the techniques proposed for microarray datasets to work on multiclass classification problems and on different ways to enhance the performance of learning algorithms.We attempt to understand and resolve the imbalance problem of datasets to substantiate the work of researchers working on microarray datasets.An analysis of the literature paves the way for comprehending and highlighting the multitude of challenges and issues in finding the optimal feature subset using various FS techniques.A case study is provided to demonstrate the process of implementation,in which three microarray cancer datasets are used to evaluate the classification accuracy and convergence ability of several wrappers and hybrid algorithms to identify the optimal feature subset.

关键词： Feature selection High dimensionality Learning techniques Microarray dataset

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IQR-based approach for DDoS detection and mitigation in SDN

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Defence technology（防务技术） 2023年第7期25卷 76-87页

作者： Rochak Swami Mayank Dave Virender Ranga department of computer engineering National Institute of TechnologyKurukshetraIndia department of information technology Delhi Technological UniversityDelhiIndia

Software-defined networking(SDN) is a trending networking paradigm that focuses on decoupling of the control logic from the data plane. This decoupling brings programmability and flexibility for the network management by introducing centralized infrastructure. The complete control logic resides in the controller, and thus it becomes the intellectual and most important entity of the SDN infrastructure. With these advantages, SDN faces several security issues in various SDN layers that may prevent the growth and global adoption of this groundbreaking technology. Control plane exhaustion and switch buffer overflow are examples of such security issues. Distributed denial-of-service(DDoS) attacks are one of the most severe attacks that aim to exhaust the controller’s CPU to discontinue the whole functioning of the SDN network. Hence, it is necessary to design a quick as well as accurate detection scheme to detect the attack traffic at an early stage. In this paper, we present a defense solution to detect and mitigate spoofed flooding DDoS attacks. The proposed defense solution is implemented in the SDN controller. The detection method is based on the idea of an statistical measure — Interquartile Range(IQR). For the mitigation purpose, the existing SDN-in-built capabilities are utilized. In this work, the experiments are performed considering the spoofed SYN flooding attack. The proposed solution is evaluated using different performance parameters, i.e., detection time, detection accuracy, packet_in messages, and CPU utilization. The experimental results reveal that the proposed defense solution detects and mitigates the attack effectively in different attack scenarios.

关键词： SDN DdoS IQR Controller CPU utilization Packet_in

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Analysis of community question-answering issues via machine learning and deep learning:State-of-the-art review

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CAAI Transactions on Intelligence technology 2023年第1期8卷 95-117页

作者： Pradeep Kumar Roy Sunil Saumya Jyoti Prakash Singh Snehasish Banerjee Adnan Gutub department of computer Science and engineering Indian Institute of Information TechnologySuratIndia Indian Institute of information technology DharwadIndia department of computer Science and engineering National Institute of TechnologyPatnaIndia The York Management School University of YorkYorkUK computer engineering department College of Computer&Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia

Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic interest.Scholars have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volume of content that CQAs engender.To clarify the current state of the CQA literature that has used ML and DL,this paper reports a systematic literature review.The goal is to summarise and synthesise the major themes of CQA research related to(i)questions,(ii)answers and(iii)users.The final review included 133 articles.Dominant research themes include question quality,answer quality,and expert identification.In terms of dataset,some of the most widely studied platforms include Yahoo!Answers,Stack Exchange and Stack Overflow.The scope of most articles was confined to just one platform with few cross-platform investigations.Articles with ML outnumber those with DL.Nonetheless,the use of DL in CQA research is on an upward trajectory.A number of research directions are proposed.

关键词： answer quality community question answering deep learning expert user machine learning question quality

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Deep Optimal VGG16 Based COVID-19 Diagnosis Model

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computers, Materials & Continua 2022年第1期70卷 43-58页

作者： M.Buvana K.Muthumayil S.Senthil kumar Jamel Nebhen Sultan S.Alshamrani Ihsan Ali department of computer Science and engineering PSNA College of Engineering and TechnologyDindigul624622India department of information technology PSNA College of Engineering and TechnologyDindigul624622India department of Electrical and Electronics engineering New Prince Shri Bhavani College of Engineering and TechnologyChennai600073India Prince Sattam Bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia department of information technology College of Computer and Information TechnologyTaif UniversityTaif21944Saudi Arabia department of computer System and technology Faculty of Computer Science and Information TechnologyUniversity of MalayaKuala Lumpur50603Malaysia

Coronavirus(COVID-19)outbreak was first identified in Wuhan,China in December 2019.It was tagged as a pandemic soon by the WHO being a serious public medical conditionworldwide.In spite of the fact that the virus can be diagnosed by qRT-PCR,COVID-19 patients who are affected with pneumonia and other severe complications can only be diagnosed with the help of Chest X-Ray(CXR)and Computed Tomography(CT)images.In this paper,the researchers propose to detect the presence of COVID-19 through images using Best deep learning model with various features.Impressive features like Speeded-Up Robust Features(SURF),Features from Accelerated Segment Test(FAST)and Scale-Invariant Feature Transform(SIFT)are used in the test images to detect the presence of virus.The optimal features are extracted from the images utilizing DeVGGCovNet(Deep optimal VGG16)model through optimal learning rate.This task is accomplished by exceptional mating conduct of Black Widow spiders.In this strategy,cannibalism is incorporated.During this phase,fitness outcomes are rejected and are not satisfied by the proposed model.The results acquired from real case analysis demonstrate the viability of DeVGGCovNet technique in settling true issues using obscure and testing spaces.VGG16 model identifies the imagewhich has a place with which it is dependent on the distinctions in images.The impact of the distinctions on labels during training stage is studied and predicted for test images.The proposed model was compared with existing state-of-the-art models and the results from the proposed model for disarray grid estimates like Sen,Spec,Accuracy and F1 score were promising.

关键词： COVID 19 multi-feature extraction vgg16 optimal learning rate

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Identity Governance Framework for Privileged Users

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computer Systems Science & engineering 2022年第3期40卷 995-1005页

作者： Mansour Hammoud Alruwies Shailendra Mishra Mohammed Abdul Rahman AlShehri department of information technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia department of computer engineering College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia

information technology companies have grown in size and recognized the need to protect their valuable assets.As a result,each IT application has its authentication mechanism,and an employee needs a username and password.As the number of applications increased,as a result,it became increasingly complex to manage all identities like the number of usernames and passwords of an employee.All identities had to be retrieved by users.Both the identities and the access rights associated with those identities had to be protected by an administrator.Management couldn’t even capture such access rights because they couldn’t verify things like privacy and security.Identity management can help solve this problem.The concept behind identity management is to centralize identity management and manage access identity centrally rather than multiple applications with their authentication and authorization mechanisms.In this research work,we develop governance and an identity management framework for information and technology infrastructures with privileged access management,consisting of cybersecurity policies and strategies.The results show the efficiency of the framework compared to the existing information security components.The integrated identity and access management and privileged access management enable organizations to respond to incidents and facilitate compliance.It can automate use cases that manage privileged accounts in the real world.

关键词： Privileged access management(PAM) lightweight directory access protocol(LDAP) identity management access control cyber-attack

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Distance Matrix and Markov Chain Based Sensor Localization in WSN

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computers, Materials & Continua 2022年第5期71卷 4051-4068页

作者： Omaima Bamasaq Daniyal Alghazzawi Surbhi Bhatia Pankaj Dadheech Farrukh Arslan Sudhakar Sengan Syed Hamid Hassan department of computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia department of information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia department of information Systems College of Computer Science and Information TechnologyKing Faisal UniversitySaudi Arabia department of computer Science and engineering Swami Keshvanand Institute of TechnologyManagement&GramothanJaipurRajasthanIndia University of engineering and technology LahorePakistan department of computer Science and engineering PSN College of Engineering and TechnologyTirunelveliTamilnaduIndia

Applications based on Wireless Sensor Networks(WSN)have shown to be quite useful in monitoring a particular geographic area of interest.Relevant geometries of the surrounding environment are essential to establish a successful WSN topology.But it is literally hard because constructing a localization algorithm that tracks the exact location of Sensor Nodes(SN)in a WSN is always a challenging task.In this research paper,Distance Matrix and Markov Chain(DM-MC)model is presented as node localization technique in which Distance Matrix and Estimation Matrix are used to identify the position of the node.The method further employs a Markov Chain Model(MCM)for energy optimization and interference reduction.Experiments are performed against two well-known models,and the results demonstrate that the proposed algorithm improves performance by using less network resources when compared to the existing models.Transition probability is used in the Markova chain to sustain higher energy nodes.Finally,the proposed Distance Matrix and Markov Chain model decrease energy use by 31%and 25%,respectively,compared to the existing DV-Hop and CSA methods.The experimental results were performed against two proven models,Distance VectorHop Algorithm(DV-HopA)and Crow Search Algorithm(CSA),showing that the proposed DM-MC model outperforms both the existing models regarding localization accuracy and Energy Consumption(EC).These results add to the credibility of the proposed DC-MC model as a better model for employing node localization while establishing a WSN framework.

关键词： Wireless sensor network resource optimization routing distance matrix Markov chain

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Web Security:Emerging Threats and Defense

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computer Systems Science & engineering 2022年第3期40卷 1233-1248页

作者： Abdulwahed Awad Almutairi Shailendra Mishra Mohammed AlShehri department of information technology College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia department of computer engineering College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia

Web applications have become a widely accepted method to support the internet for the past decade.Since they have been successfully installed in the business activities and there is a requirement of advanced functionalities,the configuration is growing and becoming more complicated.The growing demand and complexity also make these web applications a preferred target for intruders on the internet.Even with the support of security specialists,they remain highly problematic for the complexity of penetration and code reviewing methods.It requires considering different testing patterns in both codes reviewing and penetration testing.As a result,the number of hacked websites is increasing day by day.Most of these vulnerabilities also occur due to incorrect input validation and lack of result validation for lousy programming practices or coding errors.Vulnerability scanners for web applications can detect a few vulnerabilities in a dynamic approach.These are quite easy to use;however,these often miss out on some of the unique critical vulnerabilities in a different and static approach.Although these are time-consuming,they can find complex vulnerabilities and improve developer knowledge in coding and best practices.Many scanners choose both dynamic and static approaches,and the developers can select them based on their requirements and conditions.This research explores and provides details of SQL injection,operating system command injection,path traversal,and cross-site scripting vulnerabilities through dynamic and static approaches.It also examines various security measures in web applications and selected five tools based on their features for scanning PHP,and JAVA code focuses on SQL injection,cross-site scripting,Path Traversal,operating system command.Moreover,this research discusses the approach of a cyber-security tester or a security developer finding out vulnerabilities through dynamic and static approaches using manual and automated web vulnerability scanners.

关键词： SQL injection attack cross-site scripting attack command injection attack path traversal attack

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