Pub Date : 2021-11-24DOI: 10.1109/citisia53721.2021.9719899
Muhammad Akmal, Binod Syangtan, Amr Alchouemi
The main aim of this report is to find how data security can be improved in a cloud environment using the remote data auditing technique. The research analysis of the existing journal articles that are peer-reviewed Q1 level of articles is selected to perform the analysis.The main taxonomy that is proposed in this project is being data, auditing, monitoring, and output i.e., DAMO taxonomy that is used and includes these components. The data component would include the type of data; the auditing would ensure the algorithm that would be used at the backend and the storage would include the type of database as single or the distributed server in which the data would be stored.As a result of this research, it would help understand how the data can be ensured to have the required level of privacy and security when the third-party database vendors would be used by the organizations to maintain their data. Since most of the organizations are looking to reduce their burden of the local level of data storage and to reduce the maintenance by the outsourcing of the cloud there are still many issues that occur when there comes the time to check if the data is accurate or not and to see if the data is stored with resilience. In such a case, there is a need to use the Remote Data Auditing techniques that are quite helpful to ensure that the data which is outsourced is reliable and maintained with integrity when the information is stored in the single or the distributed servers.
{"title":"Enhancing the security of data in cloud computing environments using Remote Data Auditing","authors":"Muhammad Akmal, Binod Syangtan, Amr Alchouemi","doi":"10.1109/citisia53721.2021.9719899","DOIUrl":"https://doi.org/10.1109/citisia53721.2021.9719899","url":null,"abstract":"The main aim of this report is to find how data security can be improved in a cloud environment using the remote data auditing technique. The research analysis of the existing journal articles that are peer-reviewed Q1 level of articles is selected to perform the analysis.The main taxonomy that is proposed in this project is being data, auditing, monitoring, and output i.e., DAMO taxonomy that is used and includes these components. The data component would include the type of data; the auditing would ensure the algorithm that would be used at the backend and the storage would include the type of database as single or the distributed server in which the data would be stored.As a result of this research, it would help understand how the data can be ensured to have the required level of privacy and security when the third-party database vendors would be used by the organizations to maintain their data. Since most of the organizations are looking to reduce their burden of the local level of data storage and to reduce the maintenance by the outsourcing of the cloud there are still many issues that occur when there comes the time to check if the data is accurate or not and to see if the data is stored with resilience. In such a case, there is a need to use the Remote Data Auditing techniques that are quite helpful to ensure that the data which is outsourced is reliable and maintained with integrity when the information is stored in the single or the distributed servers.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122451319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-24DOI: 10.1109/citisia53721.2021.9719963
S. Tiwari, S. Abdullah, Rashidul Mubasher, A. Alsadoon, P. Prasad
Deep learning based on lung cancer classification has been used increasingly for the early diagnosis for several reasons such as lack of robust deep learning-based system, complexity of nodule structure, lack of proper lung segmentation technique, high false positive result, lack of best feature extraction and less amount of medical imaging data for training deep learning model, it has been difficult to get high classification performance. The aim of this paper getting high lung cancer classification performance. We introduce the Data, Classification technique and View (DCV) as main components of the system that concern for the better lung cancer classification results, along with them different intermediate components such as Lung nodule segmentation, Feature extraction, Feature reduction are also defined. These components are key for providing better classification performance result which helps radiologist for early diagnosis of lung cancer. We have proposed uses image data having different dimensionality as input to the deep learning based classifier which provides lung cancer classification to be viewed by radiologists for the early diagnosis of lung cancer.We evaluated the proposed DCV system by classifying 30 state-of-art research papers in the field of deep learning based lung cancer classification system. Through this paper, readers will get the result of deep learning based lung cancer classification system. Also, readers will understand the classification groups, validation criteria, future gaps of the 30 literature.
基于深度学习的肺癌分类越来越多地用于早期诊断，但由于基于深度学习的系统缺乏鲁棒性、结节结构复杂、缺乏适当的肺分割技术、假阳性结果高、缺乏最佳特征提取以及用于训练深度学习模型的医学影像数据量少等原因，难以获得较高的分类性能。本文的目的是获得较高的肺癌分类性能。我们引入了数据、分类技术和视图(Data, Classification technology and View, DCV)作为系统的主要组成部分，关注更好的肺癌分类结果，并定义了肺结节分割、特征提取、特征约简等不同的中间组成部分。这些组成部分是提供更好的分类性能结果的关键，有助于放射科医生早期诊断肺癌。我们建议使用具有不同维度的图像数据作为基于深度学习的分类器的输入，该分类器提供肺癌分类，供放射科医生用于肺癌的早期诊断。我们通过对基于深度学习的肺癌分类系统领域的30篇最新研究论文进行分类来评估所提出的DCV系统。通过本文，读者将得到基于深度学习的肺癌分类系统的结果。同时，读者将了解30篇文献的分类分组、验证标准、未来差距。
{"title":"DCV: A Taxonomy on Deep Learning Based Lung Cancer Classification","authors":"S. Tiwari, S. Abdullah, Rashidul Mubasher, A. Alsadoon, P. Prasad","doi":"10.1109/citisia53721.2021.9719963","DOIUrl":"https://doi.org/10.1109/citisia53721.2021.9719963","url":null,"abstract":"Deep learning based on lung cancer classification has been used increasingly for the early diagnosis for several reasons such as lack of robust deep learning-based system, complexity of nodule structure, lack of proper lung segmentation technique, high false positive result, lack of best feature extraction and less amount of medical imaging data for training deep learning model, it has been difficult to get high classification performance. The aim of this paper getting high lung cancer classification performance. We introduce the Data, Classification technique and View (DCV) as main components of the system that concern for the better lung cancer classification results, along with them different intermediate components such as Lung nodule segmentation, Feature extraction, Feature reduction are also defined. These components are key for providing better classification performance result which helps radiologist for early diagnosis of lung cancer. We have proposed uses image data having different dimensionality as input to the deep learning based classifier which provides lung cancer classification to be viewed by radiologists for the early diagnosis of lung cancer.We evaluated the proposed DCV system by classifying 30 state-of-art research papers in the field of deep learning based lung cancer classification system. Through this paper, readers will get the result of deep learning based lung cancer classification system. Also, readers will understand the classification groups, validation criteria, future gaps of the 30 literature.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116883595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-24DOI: 10.1109/CITISIA53721.2021.9719985
Khalid Alalawi, R. Athauda, R. Chiong
This paper presents a novel framework aimed at improving educational outcomes in tertiary-level courses. The framework integrates concepts from educational data mining, learning analytics and education research domains. The framework considers the entire life cycle of courses and includes processes and supporting technology artefacts. Well-established pedagogy principles such as Constructive Alignment (CA) and effective feedback principles are incorporated to the framework. Mapping of learning outcomes, assessment tasks and teaching/learning activities using CA enables generating revision/study plans and determining the progress and achievement of students, in addition to assisting with course evaluation. Student performance prediction models are used to identify students at risk of failure early on for interventions. Tools are provided for academics to select student groups for intervention and provide personalised feedback. Feedback reports are generated based on effective feedback principles. Learning analytics dashboards provide information on students' progress and course evaluation. An evaluation of the framework based on a case study and quasi-experimental design on real-world courses is outlined. This research and the framework have the potential to significantly contribute to this important field of study.
{"title":"An Innovative Framework to Improve Course and Student Outcomes","authors":"Khalid Alalawi, R. Athauda, R. Chiong","doi":"10.1109/CITISIA53721.2021.9719985","DOIUrl":"https://doi.org/10.1109/CITISIA53721.2021.9719985","url":null,"abstract":"This paper presents a novel framework aimed at improving educational outcomes in tertiary-level courses. The framework integrates concepts from educational data mining, learning analytics and education research domains. The framework considers the entire life cycle of courses and includes processes and supporting technology artefacts. Well-established pedagogy principles such as Constructive Alignment (CA) and effective feedback principles are incorporated to the framework. Mapping of learning outcomes, assessment tasks and teaching/learning activities using CA enables generating revision/study plans and determining the progress and achievement of students, in addition to assisting with course evaluation. Student performance prediction models are used to identify students at risk of failure early on for interventions. Tools are provided for academics to select student groups for intervention and provide personalised feedback. Feedback reports are generated based on effective feedback principles. Learning analytics dashboards provide information on students' progress and course evaluation. An evaluation of the framework based on a case study and quasi-experimental design on real-world courses is outlined. This research and the framework have the potential to significantly contribute to this important field of study.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134114289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-24DOI: 10.1109/CITISIA53721.2021.9719901
Harshith Shrestha, Kavindie Senanayake
This research would integrate cloud-computing technology with big data analytics for creating value and improving the analytics based on customer’s data. The aim is to improve the data processing to get better insights into the customer’s data and effectively analyse the patterns of the customers in order to fulfil the requirements of the customers for the revenue growth of the company. The objective of this research is to improve data processing using big data analytics. The three-factor taxonomy would be proposed comprised of three major components DSA (Data acquisition, Storage, and Analytics) for the management of customer’s data. The purpose is to get big insights into the customer’s data and analyse the customer’s patterns effectively by integrating cloud technology and big data analytics for the design innovation in SMEs. The expected outcome of this study will be the improved the data processing and processing of customer’s information for the design innovation in SMEs. The study contributes to the integrity, security, consistency, and amplifying the scalability of the data. The 12 research papers will be analysed in order to assess existing research and demonstrate the efficacy of DSA taxonomy. Some components of the taxonomy would be validated and even fewer would be evaluated in this study for improving the customer’s data processing in SMEs.
{"title":"Cloud-based big data analytics for improving the processing of customer’s data in SME’s","authors":"Harshith Shrestha, Kavindie Senanayake","doi":"10.1109/CITISIA53721.2021.9719901","DOIUrl":"https://doi.org/10.1109/CITISIA53721.2021.9719901","url":null,"abstract":"This research would integrate cloud-computing technology with big data analytics for creating value and improving the analytics based on customer’s data. The aim is to improve the data processing to get better insights into the customer’s data and effectively analyse the patterns of the customers in order to fulfil the requirements of the customers for the revenue growth of the company. The objective of this research is to improve data processing using big data analytics. The three-factor taxonomy would be proposed comprised of three major components DSA (Data acquisition, Storage, and Analytics) for the management of customer’s data. The purpose is to get big insights into the customer’s data and analyse the customer’s patterns effectively by integrating cloud technology and big data analytics for the design innovation in SMEs. The expected outcome of this study will be the improved the data processing and processing of customer’s information for the design innovation in SMEs. The study contributes to the integrity, security, consistency, and amplifying the scalability of the data. The 12 research papers will be analysed in order to assess existing research and demonstrate the efficacy of DSA taxonomy. Some components of the taxonomy would be validated and even fewer would be evaluated in this study for improving the customer’s data processing in SMEs.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121587790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-24DOI: 10.1109/citisia53721.2021.9719878
Aqeel Mustafa, Binod Syangtan, Angelika Maag, A. Elchouemi
Batch authentication technique and blockchain technology have been used for the IoV to maintain vehicle communication and eliminate accidents. It has been specified that blockchain technology acts as an emerging technology that establishes the wireless connection within the vehicle for effective communication. This research aims to cover the Internet of vehicle's concept by reviewing the currently published research articles that are assorted based on the technique, technology, and area of interest to have a secured internet of vehicle communication. Moreover, the research work had involved the secondary research method for collecting relevant research articles, i.e., literature review, which was dependent on the theoretical data and information. It has been analysed that the expected finding of the research work was about the security and secured connection between two vehicles to communicate easily and coherently.Moreover, this had helped in eliminating the accident cases and maintains the communication channel. Hence, it has been concluded that the batch authentication technique and blockchain technology are the significant aspects that assist in the reduction of accidents and security issues at the wireless level. This works a contributory role in investigating the current solutions, which depends on the batch authentication techniques for IoV and valuable insights for eliminating accidents. The study demonstrated a major component, i.e., Internet of vehicle data, Batch authentication process, secured authentication access, and Evaluation which is further evaluated to examine the system efficiency. The system architecture was also designed by considering different components and techniques that maintain the security level through batch authentication. Further, the system was verified through a term frequency graph demonstrating the frequent number of terms repeated in the review section.
{"title":"A review of Blockchain-based batch authentication techniques for securing the Internet of Vehicles","authors":"Aqeel Mustafa, Binod Syangtan, Angelika Maag, A. Elchouemi","doi":"10.1109/citisia53721.2021.9719878","DOIUrl":"https://doi.org/10.1109/citisia53721.2021.9719878","url":null,"abstract":"Batch authentication technique and blockchain technology have been used for the IoV to maintain vehicle communication and eliminate accidents. It has been specified that blockchain technology acts as an emerging technology that establishes the wireless connection within the vehicle for effective communication. This research aims to cover the Internet of vehicle's concept by reviewing the currently published research articles that are assorted based on the technique, technology, and area of interest to have a secured internet of vehicle communication. Moreover, the research work had involved the secondary research method for collecting relevant research articles, i.e., literature review, which was dependent on the theoretical data and information. It has been analysed that the expected finding of the research work was about the security and secured connection between two vehicles to communicate easily and coherently.Moreover, this had helped in eliminating the accident cases and maintains the communication channel. Hence, it has been concluded that the batch authentication technique and blockchain technology are the significant aspects that assist in the reduction of accidents and security issues at the wireless level. This works a contributory role in investigating the current solutions, which depends on the batch authentication techniques for IoV and valuable insights for eliminating accidents. The study demonstrated a major component, i.e., Internet of vehicle data, Batch authentication process, secured authentication access, and Evaluation which is further evaluated to examine the system efficiency. The system architecture was also designed by considering different components and techniques that maintain the security level through batch authentication. Further, the system was verified through a term frequency graph demonstrating the frequent number of terms repeated in the review section.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129838632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-24DOI: 10.1109/citisia53721.2021.9719941
Aman Kaushik, Nitin Jain
The commercial justification for blockchain innovation is based on appropriated data sets and smart contracts. By eliminating the need for delegates, the distributed record innovation disrupts the proprietorship model. When combined with other creative breakthroughs, such as artificial intelligence (AI) and additional material fabrication, it has the potential to have a significant impact on cross-hierarchical cycle computerization. As the blockchain innovation concept has gained traction in recent years, a growing number of companies have jumped on board. To help enable straightforwardness, productive data exchange, and cleanliness, the coordination and inventory network of the board’s company has also realised its latent capacity application potential. Only a small number of companies have identified possible blockchain use cases that would outweigh the benefits of current IT systems. Advanced pioneers and senior leaders are certain about the benefits of blockchain innovation in meetings they lead. The selection is influenced by many variables, such as an immature environment, the lack of a management paradigm, and administrative vulnerability. In order to enable permanent record sharing and observation while still maintaining specific information security, the suggested system incorporates a crossover architecture of private and public blockchains.
{"title":"An Approach For Improving Transparency And Traceability of Industrial Supply Chain With Block chain Technology","authors":"Aman Kaushik, Nitin Jain","doi":"10.1109/citisia53721.2021.9719941","DOIUrl":"https://doi.org/10.1109/citisia53721.2021.9719941","url":null,"abstract":"The commercial justification for blockchain innovation is based on appropriated data sets and smart contracts. By eliminating the need for delegates, the distributed record innovation disrupts the proprietorship model. When combined with other creative breakthroughs, such as artificial intelligence (AI) and additional material fabrication, it has the potential to have a significant impact on cross-hierarchical cycle computerization. As the blockchain innovation concept has gained traction in recent years, a growing number of companies have jumped on board. To help enable straightforwardness, productive data exchange, and cleanliness, the coordination and inventory network of the board’s company has also realised its latent capacity application potential. Only a small number of companies have identified possible blockchain use cases that would outweigh the benefits of current IT systems. Advanced pioneers and senior leaders are certain about the benefits of blockchain innovation in meetings they lead. The selection is influenced by many variables, such as an immature environment, the lack of a management paradigm, and administrative vulnerability. In order to enable permanent record sharing and observation while still maintaining specific information security, the suggested system incorporates a crossover architecture of private and public blockchains.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130154579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-24DOI: 10.1109/CITISIA53721.2021.9719887
Pranati Rakshit, Srestha Sarkar, Sambit Khan, Pritam Saha, Sonali Bhattacharyya, Nilarpan Dey, Sardar M. N. Islam, Souvik Pal
Forest fire has several devastating effects on the natural vegetation and the forest lives. The forest fire plays an important role in everyone’s lives and also in our environment. Forest fire is an integral part of many ecosystems such as grassland, temperate forest etc. The ability to predict the area where the forest fire may occur will help in optimizing the situation. The paper presented the prediction of forest fire risk with the help of a machine learning algorithm by using meteorological data. From the existing literature and Limitations, we can show that Different studies have shown the amount of burnt area due to the forest fire, and many have proposed different models to predict forest fire. But there is no such literature which predicts the depth of risk for this forest fire specifically. For that reason, the objective of this work is to predict the risk of forest fire by identifying the particular area as highly prone, moderately prone, low prone and no fire prone area. As a Present Research, in this paper we have worked with different classification models to check which models work best to predict forest fire with greater accuracy. The results we have obtained with the help of various classifiers in machine learning are much better and reliable than the results obtained by traditional computing methods. Thus, this paper indicates a deeper investigation in the field of predicting forest fire risk through machine learning. As a contribution, in this paper we have used SVM, KNN, Decision Tree, Naive Bayes classifier for prediction purposes. The main objective of this paper is to predict the possibility of forest fire with its intensity in specific atmospheric conditions in a given location. We have made comparison of the performance analysis of the different machine learning classifiers. At the end of the abstract, we got the highest AUC value of 0.99 and classification accuracy of 0.98 using Decision Tree to predict the same.
{"title":"Prediction of Forest Fire Using Machine Learning Algorithms: The Search for the Better Algorithm","authors":"Pranati Rakshit, Srestha Sarkar, Sambit Khan, Pritam Saha, Sonali Bhattacharyya, Nilarpan Dey, Sardar M. N. Islam, Souvik Pal","doi":"10.1109/CITISIA53721.2021.9719887","DOIUrl":"https://doi.org/10.1109/CITISIA53721.2021.9719887","url":null,"abstract":"Forest fire has several devastating effects on the natural vegetation and the forest lives. The forest fire plays an important role in everyone’s lives and also in our environment. Forest fire is an integral part of many ecosystems such as grassland, temperate forest etc. The ability to predict the area where the forest fire may occur will help in optimizing the situation. The paper presented the prediction of forest fire risk with the help of a machine learning algorithm by using meteorological data. From the existing literature and Limitations, we can show that Different studies have shown the amount of burnt area due to the forest fire, and many have proposed different models to predict forest fire. But there is no such literature which predicts the depth of risk for this forest fire specifically. For that reason, the objective of this work is to predict the risk of forest fire by identifying the particular area as highly prone, moderately prone, low prone and no fire prone area. As a Present Research, in this paper we have worked with different classification models to check which models work best to predict forest fire with greater accuracy. The results we have obtained with the help of various classifiers in machine learning are much better and reliable than the results obtained by traditional computing methods. Thus, this paper indicates a deeper investigation in the field of predicting forest fire risk through machine learning. As a contribution, in this paper we have used SVM, KNN, Decision Tree, Naive Bayes classifier for prediction purposes. The main objective of this paper is to predict the possibility of forest fire with its intensity in specific atmospheric conditions in a given location. We have made comparison of the performance analysis of the different machine learning classifiers. At the end of the abstract, we got the highest AUC value of 0.99 and classification accuracy of 0.98 using Decision Tree to predict the same.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123633166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-24DOI: 10.1109/CITISIA53721.2021.9719886
Teja Goud Allam, A. B. M. Mehedi Hasan, Angelika Maag, P. Prasad
The distributed ledger technology eliminates third party providers from the transaction system to enhance strength and store information using digital storage techniques. In this research paper, we incorporate distributed ledger technology and Blockchain for secure financial transactions. This technology protectively transfers information and solves other issues. It carries an extra investigation process in a smart logistic area to enhance the overall system. This research paper follows some steps to generate an infrastructure that contains four major elements. These are - input, analysis, evolution, and output. It is also useful to implement a peer-to-peer networking approach in digital currency modules. It helps to transfer currency from one account to another with more stability and security. Here researchers also provide bitcoin techniques for the international market using Blockchain and distributed ledger technology. It is applicable for the KYC system and data management. In this paper, we provide a detailed literature review on this topic and generate an evolution table. This research paper’s verification table contains the frequency of each component selected from previously published research papers. The discussion part of the paper provides a helpful approach to manage transformation data using private as well as public Blockchain.
{"title":"Ledger Technology of Blockchain and its Impact on Operational Performance of Banks: A Review","authors":"Teja Goud Allam, A. B. M. Mehedi Hasan, Angelika Maag, P. Prasad","doi":"10.1109/CITISIA53721.2021.9719886","DOIUrl":"https://doi.org/10.1109/CITISIA53721.2021.9719886","url":null,"abstract":"The distributed ledger technology eliminates third party providers from the transaction system to enhance strength and store information using digital storage techniques. In this research paper, we incorporate distributed ledger technology and Blockchain for secure financial transactions. This technology protectively transfers information and solves other issues. It carries an extra investigation process in a smart logistic area to enhance the overall system. This research paper follows some steps to generate an infrastructure that contains four major elements. These are - input, analysis, evolution, and output. It is also useful to implement a peer-to-peer networking approach in digital currency modules. It helps to transfer currency from one account to another with more stability and security. Here researchers also provide bitcoin techniques for the international market using Blockchain and distributed ledger technology. It is applicable for the KYC system and data management. In this paper, we provide a detailed literature review on this topic and generate an evolution table. This research paper’s verification table contains the frequency of each component selected from previously published research papers. The discussion part of the paper provides a helpful approach to manage transformation data using private as well as public Blockchain.","PeriodicalId":252063,"journal":{"name":"2021 6th International Conference on Innovative Technology in Intelligent System and Industrial Applications (CITISIA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126577590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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