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Blockchain-based DDoS attack mitigation protocol for device-to-device interaction in smart home

Digital Communications and Networks 2023年第2期9卷 383-392页

作者： Bello Musa Yakubu Majid Iqbal Khan Abid Khan Farhana Jabeen Gwanggil jeon Department of Mathematics and Computer Science Chulalongkorn UniversityBangkok10330Thailand Department of Computer Science COMSATS University Islamabad(CUI)Islamabad45550Pakistan College of Science and Engineering University of DerbyDerbyDE221GBUnited Kingdom Department of Embedded Systems Engineering Incheon National UniversityIncheon22012South Korea

Smart home devices are vulnerable to a variety of *** matter gets more complicated when a number of devices collaborate to launch a colluding attack(e.g.,Distributed-Denial-of-service(DDoS))in a network(e.g.,Smart home).To handle these attacks,most studies have hitherto proposed authentication protocols that cannot necessarily be implemented in devices,especially during Device-to-Device(D2D)*** into the potential of Ethereum blockchain and smart contracts,this work proposes a lightweight authentication mechanism that enables safe D2D interactions in a smart *** Ethereum blockchain enables the implementation of a decentralized prototype as well as a peer-to-peer distributed ledger *** work also uses a single server queuing system model and the authentication mechanism to curtail DDoS attacks by controlling the number of service requests in the *** simulation was conducted twenty times,each with varying number of devices chosen at random(ranging from 1 to 30).Each requester device sends an arbitrary request with a unique resource requirement at a *** is done to measure the system's consistency across a variety of device *** experimental results show that the proposed protocol not only prevents colluding attacks,but also outperforms the benchmark protocols in terms of computational cost,message processing,and response times.

关键词： DDoS attack Device-to-device Smart homes Blockchain Authentication Ethereum smartcontract

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Topic Modeling Based Warning Prioritization from Change sets of Software Repository

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Journal of Computer Science & Technology 2020年第6期35卷 1461-1479页

作者： Jung-been Lee Taek Lee Hoh Peter In College of Informatics Korea UniversitySeoul 02841Korea College of Knowledge-Based services Engineering Sungshin UniversitySeoul 02844Korea

Many existing warning prioritization techniques seek to reorder the static analysis warnings such that true positives are provided first. However, excessive amount of time is required therein to investigate and fix prioritized warnings because some are not actually true positives or are irrelevant to the code context and topic. In this paper, we propose a warning prioritization technique that reflects various latent topics from bug-related code blocks. Our main aim is to build a prioritization model that comprises separate warning priorities depending on the topic of the change sets to identify the number of true positive warnings. For the performance evaluation of the proposed model, we employ a performance metric called warning detection rate, widely used in many warning prioritization studies, and compare the proposed model with other competitive techniques. Additionally, the effectiveness of our model is verified via the application of our technique to eight industrial projects of a real global company.

关键词： automated static analysis topic modeling warning prioritization

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Simply Fine-Tuned Deep Learning-Based Classification for Breast Cancer with Mammograms

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Computers, Materials & Continua 2022年第12期73卷 4677-4693页

作者： Vicky Mudeng Jin-woo jeong se-woon Choe Department of Medical IT Convergence Engineering Kumoh National Institute of TechnologyGumi39253Korea Department of Electrical Engineering Institut Teknologi KalimantanBalikpapan76127Indonesia Department of Data Science Seoul National University of Science and TechnologySeoul01811Korea Department of IT Convergence Engineering Kumoh National Institute of TechnologyGumi39253Korea

A lump growing in the breast may be referred to as a breast mass related to the ***,not all tumors are cancerous or *** masses can cause discomfort and pain,depending on the size and texture of the *** an appropriate diagnosis,non-cancerous breast masses can be diagnosed earlier to prevent their cultivation from being *** the development of the artificial neural network,the deep discriminative model,such as a convolutional neural network,may evaluate the breast lesion to distinguish benign and malignant cancers frommammogram breast masses *** work accomplished breastmasses classification relative to benign and malignant cancers using a digital database for screening mammography image datasets.A residual neural network 50(ResNet50)model along with an adaptive gradient algorithm,adaptive moment estimation,and stochastic gradient descent optimizers,as well as data augmentations and fine-tuning methods,were *** addition,a learning rate scheduler and 5-fold cross-validation were applied with 60 training procedures to determine the best *** results of training accuracy,p-value,test accuracy,area under the curve,sensitivity,precision,F1-score,specificity,and kappa for adaptive gradient algorithm 25%,75%,100%,and stochastic gradient descent 100%fine-tunings indicate that the classifier is feasible for categorizing breast cancer into benign and malignant from the mammographic breast masses images.

关键词： Medical image analysis convolutional neural network mammogram breast masses breast cancer

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A Blockchain-Based Trust Model for Supporting Collaborative Healthcare Data Management

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Computer Systems Science & Engineering 2023年第9期46卷 3403-3421页

作者： Jiwon jeon Junho Kim Mincheol Shin Mucheol Kim Department of Computer Science and Engineering Chung-Ang UniversitySeoul06911Korea

The development of information technology allows the collaborative business process to be run across multiple enterprises in a larger market ***,while collaborative business expands the realm of businesses,it also causes various hazards in collaborative Interaction,such as data falsification,inconstancy,*** solve these issues,a blockchainbased collaborative business modeling approach was proposed and ***,the existing studies lack the blockchain risk problem-solving specification,and there is no verification technique to examine the ***,it is difficult to confirm the appropriateness of the ***,here,we propose and build a blockchain-based trust model to strengthen and verify the integrity and security of the collaborative business process;Integrity and security address the validity of collaborative interactions in terms of a trust,and we construct a blockchain pattern based on trust elements to meet the required the ***,a trust model can be applied to the healthcare data-sharing process,and then the achievement of the trustbased safe data-sharing process can be *** model can be used as a trust-building guidance tool or for integrity and security verification with the collaborative business process in a distributed environment with blockchain.

关键词： Blockchain business process trustmodel healthcare data-sharing data science

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Elbow Dislocation in Children: About Two Cases and Review of the Literature

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Open Journal of Pediatrics 2024年第2期14卷 218-226页

作者： Nyanit Bob Dorcas Atangana Cédric Paterson Mantho Fopa Pauline Kouna TsalaIrène Nadine Mvouni Bob Thérèse Raissa Bekima King Francis Ateaze Chrisantus Dikongue Diwondi Audrey Ndongo Réné Akoa Manga Ismael Evoni Molo Tatiana Choupo Guetchuin Stéphane Handy Eone Daniel Department of Surgery and Specialties Faculty of Medecine and Biomedical Sciences University of Yaoundé I Yaoundé Cameroon Infant Surgery Department of Yaounde Central Hospital Yaoundé Cameroon Faculty of Medecine and Pharmaceutical Sciences of Douala Douala Cameroon Troyes Hospital Center Troyes France Vire Normandie Hospital Center Normandie France Traumatology Department of Yaounde Central Hospital Yaoundé Cameroon

Background: Elbow dislocations in pediatric patients are rare injuries. This is a therapeutic emergency because a delay in treatment can have disastrous consequences on the functional level of the upper limb. Objective: To present the management of elbow dislocation in children in cases of limited resources. Presentation of the Cases: These were 2 older male children aged 7 and 9 years old, admitted to the emergency room for painful functional impotence of the right elbow after a fall and landing on the right hand. Clinical and radiological examinations were in favor of posterior elbow dislocations. The reductions were carried out under sedation and immobilization in Jersey. According to Robert’s criteria, the functional result was excellent in both patients. Conclusion: Emergency reduction and immobilization whatever the means ensure an excellent functional prognosis even in cases of limited resources.

关键词： Elbow Dislocation Child Diagnosis Treatment Limited Resources

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Machine Learning-Based Efficient Discovery of Software Vulnerability for Internet of Things

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Intelligent Automation & Soft Computing 2023年第8期37卷 2407-2419页

作者： So-Eun jeon Sun-Jin Lee Il-Gu Lee Department of Future Convergence Technology Engineering Sungshin Women’s UniversitySeoul02844Korea

With the development of the 5th generation of mobile communi-cation(5G)networks and artificial intelligence(AI)technologies,the use of the Internet of Things(IoT)has expanded throughout *** IoT networks have improved industrial productivity and convenience,they are highly dependent on nonstandard protocol stacks and open-source-based,poorly validated software,resulting in several security ***-ever,conventional AI-based software vulnerability discovery technologies cannot be applied to IoT because they require excessive memory and com-puting *** study developed a technique for optimizing training data size to detect software vulnerabilities rapidly while maintaining learning *** results using a software vulnerability classification dataset showed that different optimal data sizes did not affect the learning performance of the learning ***,the minimal data size required to train a model without performance degradation could be determined in *** example,the random forest model saved 85.18%of memory and improved latency by 97.82%while maintaining a learning accuracy similar to that achieved when using 100%of data,despite using only 1%.

关键词： Lightweight devices machine learning deep learning software vulnerability detection common weakness enumeration

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An Improved Time Feedforward Connections Recurrent Neural Networks

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Intelligent Automation & Soft Computing 2023年第6期36卷 2743-2755页

作者： Jin Wang Yongsong Zou se-Jung Lim School of Hydraulic&Environmental Engineering Changsha University of Science&TechnologyChangsha410014China School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410014China AI Liberal Arts Studies Division of ConvergenceHonam UniversityGwangju-si62399Korea

Recurrent Neural Networks(RNNs)have been widely applied to deal with temporal problems,such as flood forecasting and financial data *** the one hand,traditional RNNs models amplify the gradient issue due to the strict time serial dependency,making it difficult to realize a long-term memory *** the other hand,RNNs cells are highly complex,which will signifi-cantly increase computational complexity and cause waste of computational resources during model *** this paper,an improved Time Feedforward Connections Recurrent Neural Networks(TFC-RNNs)model was first proposed to address the gradient issue.A parallel branch was introduced for the hidden state at time t−2 to be directly transferred to time t without the nonlinear transforma-tion at time t−*** is effective in improving the long-term dependence of ***,a novel cell structure named Single Gate Recurrent Unit(SGRU)was *** cell structure can reduce the number of parameters for RNNs cell,consequently reducing the computational ***,applying SGRU to TFC-RNNs as a new TFC-SGRU model solves the above two ***,the performance of our proposed TFC-SGRU was verified through sev-eral experiments in terms of long-term memory and anti-interference *** results demonstrated that our proposed TFC-SGRU model can cap-ture helpful information with time step 1500 and effectively filter out the *** TFC-SGRU model accuracy is better than the LSTM and GRU models regarding language processing ability.

关键词： Time feedforward connections long-short term memory gated recurrent unit SGRU RNNs

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Energy Theft Detection in Smart Grids:Taxonomy,Comparative Analysis,Challenges,and Future Research Directions

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 578-600页

作者： Mohsin Ahmed Abid Khan Mansoor Ahmed Mouzna Tahir Gwanggil jeon Giancarlo Fortino Francesco Piccialli the Department of Computer Science COMSATS University Islamabad the Department of Computer Science School of ComputingEngineering and Digital TechnologiesTeesside University the Innovative Value Institute Maynooth University the Department of Computer Science Bahria University the School of Electronic Engineering Xidian University the Department of Embedded Systems Engineering Incheon National University IEEE the Department of Informatics ModelingElectronics and SystemsUniversity of Calabria the Department of Mathematics and Applications“R.Caccioppoli” University of Naples FedericoⅡ

Electricity theft is one of the major issues in developing countries which is affecting their economy *** with the introduction of emerging technologies,this issue became more *** many new energy theft detection(ETD)techniques have been proposed by utilising different data mining(DM)techniques,state&network(S&N)based techniques,and game theory(GT)***,a detailed survey is presented where many state-of-the-art ETD techniques are studied and analysed for their strengths and *** levels of taxonomy are presented to classify state-of-the-art ETD *** types and ways of energy theft and their consequences are studied and summarised and different parameters to benchmark the performance of proposed techniques are extracted from *** challenges of different ETD techniques and their mitigation are suggested for future *** is observed that the literature on ETD lacks knowledge management techniques that can be more effective,not only for ETD but also for theft *** can help in the prevention of energy theft,in the future,as well as for ETD.

关键词： Challenges comparative analysis energy theft detection future research directions smart grid taxonomy

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An ethnobotanical study of medicinal plants in Güce district,north-eastern Turkey

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Plant Diversity 2022年第6期44卷 577-597页

作者： Mustafa Karakose Giresun University Espiye Vocational SchoolProgramme of Medicinal and Aromatic PlantsEspiyeGiresun28600Turkey

This study aims to identify medicinal plants traditionally used to treat diseases by local people living in Güce district,north-eastern *** study was carried out between 2018 and 2021 using a two-part semi-structured,open-ended questionnaire with 165 local *** were analysed using use-report,frequency of citation,and informant consensus *** identified 128 vascular medicinal plant taxa belonging to 54 families and 106 *** most common plant taxa belong to Rosaceae(16 taxa/12.5%),Asteraceae(12 taxa/9.4%),and Lamiaceae(9 taxa/7%)*** most frequently used preparation method reported was decoction(39.8%);the most commonly utilized plant parts were leaves(40.3%).Statistical analysis reveals that women in Güce district(df?163,p?0.043sess the most traditional *** highest frequency of citation(61)and use report(92)were recorded for Tilia rubra ***,and the highest informant consensus factors were cited for respiratory system disorders(0.86),digestive system disorders(0.73),and skin disorders(0.71).This study reported nine plant taxa as medicinal plants for the first time,and documented a total of 293 new therapeutic ***,the study indicates that the transfer of traditional knowledge to future generations is limited(F?3.355,p?0.020).Action should be taken as soon as possible to preserve existing traditional knowledge and to ensure its transfer to future generations.

关键词： Colchic Ethnobotany Informant consensus factor Frequency of citation Traditional medicine Use-record

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Abnormal Behavior Detection Using Deep-Learning-Based Video Data Structuring

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Intelligent Automation & Soft Computing 2023年第8期37卷 2371-2386页

作者： Min-jeong Kim Byeong-Uk jeon Hyun Yoo Kyungyong Chung Department of Computer Science Kyonggi UniversitySuwon-si16227Gyeonggi-doKorea Contents Convergence Software Research Institute Kyonggi UniversitySuwon-si16227Gyeonggi-doKorea Division of AI Computer Science and Engineering Kyonggi UniversitySuwon-si16227Gyeonggi-doKorea

With the increasing number of digital devices generating a vast amount of video data,the recognition of abnormal image patterns has become more ***,it is necessary to develop a method that achieves this task using object and behavior information within video *** methods for detecting abnormal behaviors only focus on simple motions,therefore they cannot determine the overall behavior occurring throughout a *** this study,an abnormal behavior detection method that uses deep learning(DL)-based video-data structuring is *** and motions are first extracted from continuous images by combining existing DL-based image analysis *** weight of the continuous data pattern is then analyzed through data structuring to classify the overall *** performance of the proposed method was evaluated using varying parameter settings,such as the size of the action clip and interval between action *** model achieved an accuracy of 0.9817,indicating excellent ***,we conclude that the proposed data structuring method is useful in detecting and classifying abnormal behaviors.

关键词： Deep learning object detection abnormal behavior recognition classification data structuring

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