Pub Date : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768463
Ekata Kaushik, Vivek Prakash, O. Mahela
Power system flexibility (PSF) indicates the ability of a power network to reliably and cost-effectively manage the variability and uncertainty of demand and supply across all relevant time-scales. PSF has become a main topic of research due to increased penetration of renewable energy (RE) in the utility networks. Different methods and techniques have been explored for PSF improvement in the recent years. This paper is focussed to design an optimal restructuring of the practical transmission system to improve PSF. A power system restructuring flexibility index (PSRFI) is designed using the voltage deviations of all buses and fractional network loss to assess the flexibility level of the transmission system to feed quality power to the consumers. Study is performed for the base year 2021, projected 2031, and two proposals for network restructuring. Load projections have been carried out using least square approximation method. Cost benefit analysis is carried out to assess the payback period for investment incurred on the network restructuring. It is established that PSF has been improved significantly by optimal network restructuring.
{"title":"Power System Flexibility Improvement and Loss Reduction Using Optimal Restructuring of Transmission Network","authors":"Ekata Kaushik, Vivek Prakash, O. Mahela","doi":"10.1109/ICEEICT53079.2022.9768463","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768463","url":null,"abstract":"Power system flexibility (PSF) indicates the ability of a power network to reliably and cost-effectively manage the variability and uncertainty of demand and supply across all relevant time-scales. PSF has become a main topic of research due to increased penetration of renewable energy (RE) in the utility networks. Different methods and techniques have been explored for PSF improvement in the recent years. This paper is focussed to design an optimal restructuring of the practical transmission system to improve PSF. A power system restructuring flexibility index (PSRFI) is designed using the voltage deviations of all buses and fractional network loss to assess the flexibility level of the transmission system to feed quality power to the consumers. Study is performed for the base year 2021, projected 2031, and two proposals for network restructuring. Load projections have been carried out using least square approximation method. Cost benefit analysis is carried out to assess the payback period for investment incurred on the network restructuring. It is established that PSF has been improved significantly by optimal network restructuring.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124152872","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768546
Nadeem Akram, V. Ilango
The Evolution of Web over the years has made a significant progress on how the information is organized and stored, as the complexity of the data stored and retrieved increases it becomes mandatory to upgrade the methodology involved in achieving them. During web Access it becomes essential to determine the nature of the user so as to understand his preferences in order to generate a customized look and feel of the website and there by offering him a Personalized web surfing experience. The primary Stage of a customized web access is in determining what the user wants from the web via a proper semantic Query Methodology which represents what user need rather than content prevailing in the web for request Query. When the user request is understood, the next task would to categorize the possible results in response to the query depending upon relevance. Furthermore, the process would be to categorize user data according different aspects to create web personalization. This takes the web to next level with web usage prediction using Web log files there by creating a New Customized web for every one with the major focus to represent what matters to the users.
{"title":"Intelligent Web Mining Techniques using Semantic Web","authors":"Nadeem Akram, V. Ilango","doi":"10.1109/ICEEICT53079.2022.9768546","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768546","url":null,"abstract":"The Evolution of Web over the years has made a significant progress on how the information is organized and stored, as the complexity of the data stored and retrieved increases it becomes mandatory to upgrade the methodology involved in achieving them. During web Access it becomes essential to determine the nature of the user so as to understand his preferences in order to generate a customized look and feel of the website and there by offering him a Personalized web surfing experience. The primary Stage of a customized web access is in determining what the user wants from the web via a proper semantic Query Methodology which represents what user need rather than content prevailing in the web for request Query. When the user request is understood, the next task would to categorize the possible results in response to the query depending upon relevance. Furthermore, the process would be to categorize user data according different aspects to create web personalization. This takes the web to next level with web usage prediction using Web log files there by creating a New Customized web for every one with the major focus to represent what matters to the users.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124143398","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768638
Dengke Li
For synchronous reluctance motors, there are more and more researches on position sensorless vector control. However, when starting at zero speed or low speed, some problems are often encountered. These problems often affect the overall control effect of the synchronous reluctance motor. To improve the control effect, this paper studies the starting effect of the synchronous reluctance motors. Using the salient pole characteristics of the synchronous reluctance motors, the method used in this article is the rotation high-frequency voltage signal injection method. The high-frequency sine (cosine) signal is injected into two-phase stationary coordinate system of the motor at the same time. The actual rotor position angle will be obtained from the response current. Simulation uses this method and the simulation results respectively show the zero-speed and low-speed startup effects. This method can accurately estimate the rotor angle and realize zero-speed and low-speed starting. These results verify the correctness of the method.
{"title":"Research on Zero and Low Speed Startup of Synchronous Reluctance Motor Based on High Frequency Injection Method","authors":"Dengke Li","doi":"10.1109/ICEEICT53079.2022.9768638","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768638","url":null,"abstract":"For synchronous reluctance motors, there are more and more researches on position sensorless vector control. However, when starting at zero speed or low speed, some problems are often encountered. These problems often affect the overall control effect of the synchronous reluctance motor. To improve the control effect, this paper studies the starting effect of the synchronous reluctance motors. Using the salient pole characteristics of the synchronous reluctance motors, the method used in this article is the rotation high-frequency voltage signal injection method. The high-frequency sine (cosine) signal is injected into two-phase stationary coordinate system of the motor at the same time. The actual rotor position angle will be obtained from the response current. Simulation uses this method and the simulation results respectively show the zero-speed and low-speed startup effects. This method can accurately estimate the rotor angle and realize zero-speed and low-speed starting. These results verify the correctness of the method.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123723286","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768631
S. Prabha, K. Chandu, Anusha Sairam, M. V. Ratna kumar, K. Sankaran
Abnormal cell growth in brain causes brain tumor which may be a cancerous or non-cancerous one. Tumors can start in the brain, or cancer elsewhere in the body can spread to the brain. This tumor has to be detected at an early stage when it is small. Tumor can be detected easily with the help of MRI modality as the resolution and quality of an image is superior in MRI liken with other imagining techniques and also it is not harmful for the tissues that are present in the brain. In our proposed methodology, three sections have been implemented which includes segmentation, feature extraction and classification. Employment of region based active contour algorithm is used to identify the type of tumors as malignant and benign. Thus, proposed system classifies tumor with an accuracy of 93.34 %.
{"title":"Brain Tumor Analysis using Machine Learning Techniques","authors":"S. Prabha, K. Chandu, Anusha Sairam, M. V. Ratna kumar, K. Sankaran","doi":"10.1109/ICEEICT53079.2022.9768631","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768631","url":null,"abstract":"Abnormal cell growth in brain causes brain tumor which may be a cancerous or non-cancerous one. Tumors can start in the brain, or cancer elsewhere in the body can spread to the brain. This tumor has to be detected at an early stage when it is small. Tumor can be detected easily with the help of MRI modality as the resolution and quality of an image is superior in MRI liken with other imagining techniques and also it is not harmful for the tissues that are present in the brain. In our proposed methodology, three sections have been implemented which includes segmentation, feature extraction and classification. Employment of region based active contour algorithm is used to identify the type of tumors as malignant and benign. Thus, proposed system classifies tumor with an accuracy of 93.34 %.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122378207","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768409
M. Paul, S. Tamilselvan, T. Venkatesan
In inventory control theory the one of the important model is to estimate the conserve inventory when the stations are in series. In this model a system with two nodes are suggested. In the first phase it is assumed that there is only machine A1 and the second phase as two machines say $B_{2}^{1}$ and $B_{2}^{11}$. The machines in the second stage may have same or different process types. During the breakdown time of the machine in the first stage a reserve inventory is maintained to ensure uninterrupted production in the next stage. This conserve inventory is needed as otherwise; the machines in the second stage may become idle which will impact not only the profits but also bring loss due to non-functioning of machines. Mathematical models has been derived for obtaining conserve inventory by treating repair time and inter arrival time as random variables
{"title":"Optimal Conserve Inventory from One Outturn Gizmos to Two Intake Gizmos When Inter-Arrival Breakdown is a Random Variable","authors":"M. Paul, S. Tamilselvan, T. Venkatesan","doi":"10.1109/ICEEICT53079.2022.9768409","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768409","url":null,"abstract":"In inventory control theory the one of the important model is to estimate the conserve inventory when the stations are in series. In this model a system with two nodes are suggested. In the first phase it is assumed that there is only machine A1 and the second phase as two machines say $B_{2}^{1}$ and $B_{2}^{11}$. The machines in the second stage may have same or different process types. During the breakdown time of the machine in the first stage a reserve inventory is maintained to ensure uninterrupted production in the next stage. This conserve inventory is needed as otherwise; the machines in the second stage may become idle which will impact not only the profits but also bring loss due to non-functioning of machines. Mathematical models has been derived for obtaining conserve inventory by treating repair time and inter arrival time as random variables","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128228399","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768417
Atul Nayan, O. P. Rahi
Microgrids are the major component of the future smart grid, as these open up new possibilities for aggregating loads and sources. As a result, it is considered to be the next-generation power system arrangement, capable of operating in both standalone and grid-connected modes. This work describes a novel fuzzy logic controller for controlling the charging and discharging of a PV battery storage system. The battery is charged and discharged based on the power difference between generation and demand. There are numerous strategies for controlling the performance of battery, however these controlling techniques have issues in terms of limiting overcharging, complexity in control and slow charging. The paper compares the performance of battery, simulated in MATLAB Simulink using PID controller and fuzzy logic controller. A fuzzy logic controller is less complex to design and provides fast charging.
{"title":"Charging and Discharging of Battery in a PV System using Fuzzy Logic Controller","authors":"Atul Nayan, O. P. Rahi","doi":"10.1109/ICEEICT53079.2022.9768417","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768417","url":null,"abstract":"Microgrids are the major component of the future smart grid, as these open up new possibilities for aggregating loads and sources. As a result, it is considered to be the next-generation power system arrangement, capable of operating in both standalone and grid-connected modes. This work describes a novel fuzzy logic controller for controlling the charging and discharging of a PV battery storage system. The battery is charged and discharged based on the power difference between generation and demand. There are numerous strategies for controlling the performance of battery, however these controlling techniques have issues in terms of limiting overcharging, complexity in control and slow charging. The paper compares the performance of battery, simulated in MATLAB Simulink using PID controller and fuzzy logic controller. A fuzzy logic controller is less complex to design and provides fast charging.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128441607","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768441
M. Geetha, R. Suganthe, S Roselin Nivetha, R. Anju, R. Anuradha, J. Haripriya
Cauvery delta zone in Tamilnadu is called as “Nerkazhanchiyam” (the land of Paddy) of the state, as it has the potential to produce paddy in huge quantity that can be suffice the need of the state. This zone includes the districts such as Thanjavur, Tiruvarur, Nagapattinam, Trichy and Cuddalore. These districts account for about 53% of production of paddy in the state. Increasing the production of paddy in Cauvery Delta Zone would satisfy the requirement of rice in the state on the whole. This will also have a substantial influence on both the farmer's and the nation's economy. Forecasting the production of crops beforehand could assist the farmers in improving their productivity. This necessitates the design of a precise crop yield prediction model. Crop production in agriculture is primarily determined by a variety of factors that falls under three categories: technological (agricultural techniques, managerial decisions, etc.), biological (diseases, insects, pests, etc.), and environmental (climate change, etc.). Among these factors environmental factors pose a great challenge to the decision makers in developing a precise prediction model. Hence, it is proposed to develop a suitable yield prediction model to predict the yield of paddy in Cauvery delta region considering the environmental factors along with the supplied nutrients. The proposed prediction model makes use of Long Short Term Memory (LSTM) algorithm which is a popular deep learning algorithm, to forecast the yield of paddy. LSTM is well known for its better prediction using time series data. Performance of the proposed prediction model is measured using the training loss and validation loss.
{"title":"A Time-Series Based Yield Forecasting Model Using Stacked Lstm To Predict The Yield Of Paddy In Cauvery Delta Zone In Tamilnadu","authors":"M. Geetha, R. Suganthe, S Roselin Nivetha, R. Anju, R. Anuradha, J. Haripriya","doi":"10.1109/ICEEICT53079.2022.9768441","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768441","url":null,"abstract":"Cauvery delta zone in Tamilnadu is called as “Nerkazhanchiyam” (the land of Paddy) of the state, as it has the potential to produce paddy in huge quantity that can be suffice the need of the state. This zone includes the districts such as Thanjavur, Tiruvarur, Nagapattinam, Trichy and Cuddalore. These districts account for about 53% of production of paddy in the state. Increasing the production of paddy in Cauvery Delta Zone would satisfy the requirement of rice in the state on the whole. This will also have a substantial influence on both the farmer's and the nation's economy. Forecasting the production of crops beforehand could assist the farmers in improving their productivity. This necessitates the design of a precise crop yield prediction model. Crop production in agriculture is primarily determined by a variety of factors that falls under three categories: technological (agricultural techniques, managerial decisions, etc.), biological (diseases, insects, pests, etc.), and environmental (climate change, etc.). Among these factors environmental factors pose a great challenge to the decision makers in developing a precise prediction model. Hence, it is proposed to develop a suitable yield prediction model to predict the yield of paddy in Cauvery delta region considering the environmental factors along with the supplied nutrients. The proposed prediction model makes use of Long Short Term Memory (LSTM) algorithm which is a popular deep learning algorithm, to forecast the yield of paddy. LSTM is well known for its better prediction using time series data. Performance of the proposed prediction model is measured using the training loss and validation loss.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129945062","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768508
Nilay Ganatra, Sanskruti Patel, Rachana Patel, S. Khant, Atul Patel
Automatic facial expression classification is very demanding research field because of its application in the field of health, safety and human machine interfaces. Many attempts by the researchers have been made in developing methodologies which can interpret, decode facial expression and obtain important features from the facial images to achieve better classification result. With the advancement in the data capturing techniques and various deep learning architectures it is possible to achieve higher accuracy in the computer vision task like facial expression classification. The aim of this research paper is to propose Custom-CNN architecture for the facial expression classification and performance of the model is compared with other standard pre-trained deep convolutional neural networks. Kaggle dataset comprises 35,900 is utilized to train, validate and test CNN models.
{"title":"Classification of Facial Expression for Emotion Recognition using Convolutional Neural Network","authors":"Nilay Ganatra, Sanskruti Patel, Rachana Patel, S. Khant, Atul Patel","doi":"10.1109/ICEEICT53079.2022.9768508","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768508","url":null,"abstract":"Automatic facial expression classification is very demanding research field because of its application in the field of health, safety and human machine interfaces. Many attempts by the researchers have been made in developing methodologies which can interpret, decode facial expression and obtain important features from the facial images to achieve better classification result. With the advancement in the data capturing techniques and various deep learning architectures it is possible to achieve higher accuracy in the computer vision task like facial expression classification. The aim of this research paper is to propose Custom-CNN architecture for the facial expression classification and performance of the model is compared with other standard pre-trained deep convolutional neural networks. Kaggle dataset comprises 35,900 is utilized to train, validate and test CNN models.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130177769","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768575
Veeraiyah Thangasamy, I. Singh, Karishma, Yaswanth, Jathin Sai
Non-Orthogonal multiple access (NOMA) scheme serves as a favorable technology for 5G and beyond cellular networks as compared to orthogonal multiple access (OMA) scheme. Multipath fading also affects the performance of wireless communication system. So as to exploit the features of NOMA technique, it is vital to identify and analyze its performance over various fading channels. This paper provides the performance analysis of NOMA based cellular system over two key parameters named as channel capacity and outage probability. Rician fading distribution has been considered for multipath fading. Rician fading channel is much suitable when at least one communication link fallow a line-of-sight (LoS) path and the signal strength is much stronger than other paths. An analytical expression for channel capacity and outage probability has been derived for considered system model. Mante Carlo simulation has been performed to obtain the simulation results for channel capacity and outage probability using the Rician fading channel. Comparison of simulation results for near and far users have been provided for channel capacity and outage probability.
{"title":"Analysis of Capacity and Outage Probability for NOMA based Cellular Communication over Rician Fading Channel","authors":"Veeraiyah Thangasamy, I. Singh, Karishma, Yaswanth, Jathin Sai","doi":"10.1109/ICEEICT53079.2022.9768575","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768575","url":null,"abstract":"Non-Orthogonal multiple access (NOMA) scheme serves as a favorable technology for 5G and beyond cellular networks as compared to orthogonal multiple access (OMA) scheme. Multipath fading also affects the performance of wireless communication system. So as to exploit the features of NOMA technique, it is vital to identify and analyze its performance over various fading channels. This paper provides the performance analysis of NOMA based cellular system over two key parameters named as channel capacity and outage probability. Rician fading distribution has been considered for multipath fading. Rician fading channel is much suitable when at least one communication link fallow a line-of-sight (LoS) path and the signal strength is much stronger than other paths. An analytical expression for channel capacity and outage probability has been derived for considered system model. Mante Carlo simulation has been performed to obtain the simulation results for channel capacity and outage probability using the Rician fading channel. Comparison of simulation results for near and far users have been provided for channel capacity and outage probability.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128855575","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768608
R. Yarava, G. Rao, Yugandhar Garapati, G. Babu, S. D. V. Prasad
The data sharing is a helpful and financial assistance provided by CC. Information substance security also rises out of it since the information is moved to some cloud workers. To ensure the sensitive and important data; different procedures are utilized to improve access manage on collective information. Here strategies, Cipher text-policyattribute based encryption (CP-ABE) might create it very helpful and safe. The conventionalCP-ABE concentrates on information privacy only; whereas client's personal security protection is a significant problem as of now. CP-ABE byhidden access (HA) strategy makes sure information privacy and ensures that client's protection isn't exposed also. Nevertheless, the vast majority of the current plans are ineffectivein correspondence overhead and calculation cost. In addition, the vast majority of thismechanism takes no thought regardingabilityauthenticationor issue of security spillescapein abilityverificationstage. To handle the issues referenced over, a security protectsCP-ABE methodby proficient influenceauthenticationis presented in this manuscript. Furthermore, its privacy keys accomplish consistent size. In the meantime, the suggestedplan accomplishes the specific safetyin decisional n-BDHE issue and decisional direct presumption. The computational outcomes affirm the benefits of introduced method.
{"title":"Analysis on the Development of Cloud Security using Privacy Attribute Data Sharing","authors":"R. Yarava, G. Rao, Yugandhar Garapati, G. Babu, S. D. V. Prasad","doi":"10.1109/ICEEICT53079.2022.9768608","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768608","url":null,"abstract":"The data sharing is a helpful and financial assistance provided by CC. Information substance security also rises out of it since the information is moved to some cloud workers. To ensure the sensitive and important data; different procedures are utilized to improve access manage on collective information. Here strategies, Cipher text-policyattribute based encryption (CP-ABE) might create it very helpful and safe. The conventionalCP-ABE concentrates on information privacy only; whereas client's personal security protection is a significant problem as of now. CP-ABE byhidden access (HA) strategy makes sure information privacy and ensures that client's protection isn't exposed also. Nevertheless, the vast majority of the current plans are ineffectivein correspondence overhead and calculation cost. In addition, the vast majority of thismechanism takes no thought regardingabilityauthenticationor issue of security spillescapein abilityverificationstage. To handle the issues referenced over, a security protectsCP-ABE methodby proficient influenceauthenticationis presented in this manuscript. Furthermore, its privacy keys accomplish consistent size. In the meantime, the suggestedplan accomplishes the specific safetyin decisional n-BDHE issue and decisional direct presumption. The computational outcomes affirm the benefits of introduced method.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124604782","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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