Pub Date : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9754077
B. Sree, N. K. Krishna Rao, Chennupalli Srinivasulu, T. P. Kumar, Valisetty Ramaneesh, J. B. Narayana, Sourav Dutta
Nowadays, Brain tumor detection has turned into a casualty in the health care sector. A tumor is a swelling or a morbid enlargement caused by an overabundant growth of cells and their division. Generally, cells grow and divide to make new cells controlled. A tumor is not the same as cancer; tumors may be malignant or premalignant. The usage of Machine Learning holds a significant stand in the medical field. Hence, Machine Learning techniques are being used efficiently to detect brain tumor and prevent it at an early stage.
{"title":"Brain Tumor Detection and Classification using Magnetic Resonance Imaging and Machine Learning Approaches","authors":"B. Sree, N. K. Krishna Rao, Chennupalli Srinivasulu, T. P. Kumar, Valisetty Ramaneesh, J. B. Narayana, Sourav Dutta","doi":"10.1109/ICCMC53470.2022.9754077","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9754077","url":null,"abstract":"Nowadays, Brain tumor detection has turned into a casualty in the health care sector. A tumor is a swelling or a morbid enlargement caused by an overabundant growth of cells and their division. Generally, cells grow and divide to make new cells controlled. A tumor is not the same as cancer; tumors may be malignant or premalignant. The usage of Machine Learning holds a significant stand in the medical field. Hence, Machine Learning techniques are being used efficiently to detect brain tumor and prevent it at an early stage.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132335226","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753747
C. T. Ashita, T. S. Kala
The WHO studies show that cardiovascular diseases (CVD) are the major cause of 31% of all global deaths. CVD is also responsible for 45 percent of deaths in people aged 40 to 69. An accurate prediction system of heart disease is necessary and important to reduce deaths, globally. Today with the advancement of technology, prediction of heart disease using deep learning models, applying vast data can give an accurate prediction model. Using a deep learning method 94% of accuracy can be obtained and the data sets with different attributes can be used for analysis. The objective is to apply various algorithms to the problem and make a comparative study on the effectiveness of these algorithms in predicting the presence of coronary illness in a person.
{"title":"Prediction of Heart Diseases using Deep Learning: A Review","authors":"C. T. Ashita, T. S. Kala","doi":"10.1109/ICCMC53470.2022.9753747","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753747","url":null,"abstract":"The WHO studies show that cardiovascular diseases (CVD) are the major cause of 31% of all global deaths. CVD is also responsible for 45 percent of deaths in people aged 40 to 69. An accurate prediction system of heart disease is necessary and important to reduce deaths, globally. Today with the advancement of technology, prediction of heart disease using deep learning models, applying vast data can give an accurate prediction model. Using a deep learning method 94% of accuracy can be obtained and the data sets with different attributes can be used for analysis. The objective is to apply various algorithms to the problem and make a comparative study on the effectiveness of these algorithms in predicting the presence of coronary illness in a person.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123371785","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753805
Yilian Li, Yunrui Ji, Jiaojiao Zhai, Xueyan Su, Meicui Fang
With the continuous deepening of my country's fiscal and taxation system reforms, my country's personal income tax collection for salary payment has undergone tremendous changes, making the personal income tax collection for salary payment more scientific and reasonable. If you want to better enjoy the content of this policy, carry out tax payment. Planning research is very necessary. Based on the speech recognition system and the background of the new tax law reform, this article analyzes the basic theories and methods of personal income tax payment and tax planning, and proposes the tax forecast and abnormality detection of student income tax under the new tax law reform. The results show that abnormalities are reduced by 7.6%.
{"title":"The Voice Recognition System Based on The Prediction and Anomaly Detection of the Individual Income Tax of College Students under the New Tax Law","authors":"Yilian Li, Yunrui Ji, Jiaojiao Zhai, Xueyan Su, Meicui Fang","doi":"10.1109/ICCMC53470.2022.9753805","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753805","url":null,"abstract":"With the continuous deepening of my country's fiscal and taxation system reforms, my country's personal income tax collection for salary payment has undergone tremendous changes, making the personal income tax collection for salary payment more scientific and reasonable. If you want to better enjoy the content of this policy, carry out tax payment. Planning research is very necessary. Based on the speech recognition system and the background of the new tax law reform, this article analyzes the basic theories and methods of personal income tax payment and tax planning, and proposes the tax forecast and abnormality detection of student income tax under the new tax law reform. The results show that abnormalities are reduced by 7.6%.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"506 Pt A 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126047744","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753914
Rui Li, Zhanying Gao
This article introduces the related theories of image stitching technology, focusing on the classic scale-invariant feature transform (SIFT) algorithm-based feature detection and description problems, and elaborates its basic theory and feature extraction process; for SIFT's existence during registration Problems such as large amount of calculation and many mismatches. A consistent point shift (CPD) image registration algorithm based on SIFT features is proposed. The general principles of art measurement and the image of template matching algorithm based on art measurement are discussed. Splicing technology and strategies to improve algorithm efficiency.
{"title":"Intelligent Analysis Framework of Art Measurement Based on Multi-Angle Image Switching Technology","authors":"Rui Li, Zhanying Gao","doi":"10.1109/ICCMC53470.2022.9753914","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753914","url":null,"abstract":"This article introduces the related theories of image stitching technology, focusing on the classic scale-invariant feature transform (SIFT) algorithm-based feature detection and description problems, and elaborates its basic theory and feature extraction process; for SIFT's existence during registration Problems such as large amount of calculation and many mismatches. A consistent point shift (CPD) image registration algorithm based on SIFT features is proposed. The general principles of art measurement and the image of template matching algorithm based on art measurement are discussed. Splicing technology and strategies to improve algorithm efficiency.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121219064","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753965
K. S. Rama Krishna, Pooja Pasula, T. Kavyakeerthi, I. Karthik
Making precise and valid sales prediction plays a vital role in any business organization. Modern methods that are used for sales prediction are often based on the historical income of a product. Further in these models, the corresponding timelines, adjustment of timelines, obtaining the comparative behavior of the product aids them for efficient demand forecasting. Since the product segmentation section on the E-trade platform consists of large numbers of related products, where the sales expert may meet, and attempts to include these series chain records into an integrated model. In this proposed model, on demand and off-demand relationship that is available on all products from the managers are considered. In addition to the forecast framework, a pre-scientific framework is also proposed to overcome the challenges of the E-trading business organizations. Comparing the predictive framework in the real-time global market is also achieved. Our approach accomplishes efficient outcomes when compared with the existing models.
{"title":"Identifying Demand Forecasting using Machine Learning for Business Intelligence","authors":"K. S. Rama Krishna, Pooja Pasula, T. Kavyakeerthi, I. Karthik","doi":"10.1109/ICCMC53470.2022.9753965","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753965","url":null,"abstract":"Making precise and valid sales prediction plays a vital role in any business organization. Modern methods that are used for sales prediction are often based on the historical income of a product. Further in these models, the corresponding timelines, adjustment of timelines, obtaining the comparative behavior of the product aids them for efficient demand forecasting. Since the product segmentation section on the E-trade platform consists of large numbers of related products, where the sales expert may meet, and attempts to include these series chain records into an integrated model. In this proposed model, on demand and off-demand relationship that is available on all products from the managers are considered. In addition to the forecast framework, a pre-scientific framework is also proposed to overcome the challenges of the E-trading business organizations. Comparing the predictive framework in the real-time global market is also achieved. Our approach accomplishes efficient outcomes when compared with the existing models.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116645190","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753898
T. Madhuri, M. S. Rao, P. S. Santosh, P. Tejaswi, S. Devendra
Wireless Body Area Network plays a major role in patient health monitoring, and controlling is the best method in the present generation. Nowadays, especially the patient’s status information plays a vital role and must also be securely covered. One of the major challenges is to provide secure transmission between nodes. This paper recommends that the confidentiality of patients’ medical data be protected by implementing two concepts called the Diffie-Hellman key generation method for different key sizes and Elliptic Curve Cryptography (ECC). A biometric authentication system is also proposed where the biometric images are used as secret keys to authenticate legitimate users and data users like doctors and patients. This system implements an asymmetric encryption algorithm that is more effective and produces a better outcome. The focal point is to produce a better performance on the wireless domain using ECC.
{"title":"Data Communication Protocol using Elliptic Curve Cryptography for Wireless Body Area Network","authors":"T. Madhuri, M. S. Rao, P. S. Santosh, P. Tejaswi, S. Devendra","doi":"10.1109/ICCMC53470.2022.9753898","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753898","url":null,"abstract":"Wireless Body Area Network plays a major role in patient health monitoring, and controlling is the best method in the present generation. Nowadays, especially the patient’s status information plays a vital role and must also be securely covered. One of the major challenges is to provide secure transmission between nodes. This paper recommends that the confidentiality of patients’ medical data be protected by implementing two concepts called the Diffie-Hellman key generation method for different key sizes and Elliptic Curve Cryptography (ECC). A biometric authentication system is also proposed where the biometric images are used as secret keys to authenticate legitimate users and data users like doctors and patients. This system implements an asymmetric encryption algorithm that is more effective and produces a better outcome. The focal point is to produce a better performance on the wireless domain using ECC.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121464674","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753738
Chingakham Nirma Devi, R. Renuga Devi
Tourism experience shared through social media has become a highly influential source of information and has a multi-faceted impact on tourism. With the vast development of the Internet, text data has become one of the leading formats of big tourism data. Text analytics of such data has great potential to express tourists' opinions effectively. Sentiment analysis is an essential component of tourism big data because it can detect positive and negative opinions in texts. Tourist comments are essential for the development of tourism but still, the number of comments complicates the analysis of essential aspects of the comments by the owner. Big data-based sentiment analysis is one of the most challenging problems globally, and the amount of data is enormous. To resolve this problem, the proposed big data approaches can help detect new words, especially with sentiment analysis and detection of proper nouns and emotional words useful for subsequent tasks as word vectors. The proposed system follows the three steps: text analysis and cleaning, Word vector similarity analysis, and final sentiment classification. First step is used to remove the noise of the data and detect the symbols. The next step is the ID3 (Iterative Dichotomiser) Maximum Word Vector Dimensionality Posteriorl method, which discovers all travel review corpora's main problem and uses it to enrich the vocabulary vector representation of words in context. Attention mechanisms are used to learn words and the overall meaning of different weights text attributes. According to the classification, the final Superior Expectation-Maximization Vector Neural Network (SEMVNN) is used for classifying sentiment analysis level. The SEMVNN method gives accuracy, time complexity, precision, recall and F-measure values to achieve better results than the previous system.
{"title":"Big Data Analytics Based Sentiment Analysis Using Superior Expectation-Maximization Vector Neural Network in Tourism","authors":"Chingakham Nirma Devi, R. Renuga Devi","doi":"10.1109/ICCMC53470.2022.9753738","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753738","url":null,"abstract":"Tourism experience shared through social media has become a highly influential source of information and has a multi-faceted impact on tourism. With the vast development of the Internet, text data has become one of the leading formats of big tourism data. Text analytics of such data has great potential to express tourists' opinions effectively. Sentiment analysis is an essential component of tourism big data because it can detect positive and negative opinions in texts. Tourist comments are essential for the development of tourism but still, the number of comments complicates the analysis of essential aspects of the comments by the owner. Big data-based sentiment analysis is one of the most challenging problems globally, and the amount of data is enormous. To resolve this problem, the proposed big data approaches can help detect new words, especially with sentiment analysis and detection of proper nouns and emotional words useful for subsequent tasks as word vectors. The proposed system follows the three steps: text analysis and cleaning, Word vector similarity analysis, and final sentiment classification. First step is used to remove the noise of the data and detect the symbols. The next step is the ID3 (Iterative Dichotomiser) Maximum Word Vector Dimensionality Posteriorl method, which discovers all travel review corpora's main problem and uses it to enrich the vocabulary vector representation of words in context. Attention mechanisms are used to learn words and the overall meaning of different weights text attributes. According to the classification, the final Superior Expectation-Maximization Vector Neural Network (SEMVNN) is used for classifying sentiment analysis level. The SEMVNN method gives accuracy, time complexity, precision, recall and F-measure values to achieve better results than the previous system.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125127006","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753880
S. A., L. Chitra, S. Chandran, B. Aravind, J. N. Kumar, S. Jayaprakash, M. Ramkumar
Due to rising environmental challenges and complicated emission regulations, electric vehicles have been seen as an alternative to traditional transportation. Modern electric vehicles use electronic circuits powered by electrical energy (PECs). DC to DC converters and DC to AC inverters are both classed as PECs. DC to AC inverter: It delivers utility power while also driving electric motors; the DC to DC converter serves as a source of low voltage utility electricity. DC to DC converters are categorised according to application requirements. In order to charge a high-power electric load, an increase in output is needed. It is because of this that it uses the SEPIC converter. DC-DC converter designates the single-ended primary-inductor converter (SEPIC). The electrical potential may be any value, such as less than, equal to, or greater than the input voltage. Duty cycle of the control transistor governs the SEPIC output. In SEPIC, voltage conversion is accomplished by transferring energy between inductors and capacitors. SEPIC boost converter relates to buck-boost converter modification. Both are comparable. The SEPIC converter has a few benefits. They are non-inverted input- same polarity of input and output voltage, between output and input, energy is linked using a series capacitor- to a short circuit output, producing greater responsiveness, genuine shutdown is possible- output goes to 0V if switch is off. This converter is simple to control while operating in CCM mode. Because both switches use the same gating pulse, the duty cycle may be adjusted to obtain a broad range of output voltage. In terms of number of components, diode and switch voltage stress, and voltage gain, recent non-coupled inductor converters are compared to the proposed converter. With regard to output voltage, the suggested converter produces a lower proportion of voltage stress on switches. When compared to existing converters, the suggested converter produces a high voltage gain with fewer components.
{"title":"Distinguished DC-DC Converter for an Electric Vehicle","authors":"S. A., L. Chitra, S. Chandran, B. Aravind, J. N. Kumar, S. Jayaprakash, M. Ramkumar","doi":"10.1109/ICCMC53470.2022.9753880","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753880","url":null,"abstract":"Due to rising environmental challenges and complicated emission regulations, electric vehicles have been seen as an alternative to traditional transportation. Modern electric vehicles use electronic circuits powered by electrical energy (PECs). DC to DC converters and DC to AC inverters are both classed as PECs. DC to AC inverter: It delivers utility power while also driving electric motors; the DC to DC converter serves as a source of low voltage utility electricity. DC to DC converters are categorised according to application requirements. In order to charge a high-power electric load, an increase in output is needed. It is because of this that it uses the SEPIC converter. DC-DC converter designates the single-ended primary-inductor converter (SEPIC). The electrical potential may be any value, such as less than, equal to, or greater than the input voltage. Duty cycle of the control transistor governs the SEPIC output. In SEPIC, voltage conversion is accomplished by transferring energy between inductors and capacitors. SEPIC boost converter relates to buck-boost converter modification. Both are comparable. The SEPIC converter has a few benefits. They are non-inverted input- same polarity of input and output voltage, between output and input, energy is linked using a series capacitor- to a short circuit output, producing greater responsiveness, genuine shutdown is possible- output goes to 0V if switch is off. This converter is simple to control while operating in CCM mode. Because both switches use the same gating pulse, the duty cycle may be adjusted to obtain a broad range of output voltage. In terms of number of components, diode and switch voltage stress, and voltage gain, recent non-coupled inductor converters are compared to the proposed converter. With regard to output voltage, the suggested converter produces a lower proportion of voltage stress on switches. When compared to existing converters, the suggested converter produces a high voltage gain with fewer components.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131503879","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753907
S. T., C. S, Ch V N S Pavan Pusya, R. Bhuvaneswari
A system for battery management is vital in reliable and safe battery operation. They are being extensively applied in high power applications, hybrid electric vehicles, and many more arenas to ensure intermittent power supply. The paper aims at providing a detailed study of the different batteries available in the market and their efficacy when exposed to different environments. The main parameters taken into consideration are the service life, nominal voltage, charging and discharging rates, and temperatures. Firstly, types of battery modeling are studied comprehensively followed by various batteries used in the industry for EVs and Power system applications. Various battery models such as electrical, thermal, and coupled electrothermal model are discussed. Subsequently, the battery condition estimates for the charging state, health estimation, and internal temperature are extensively studied. Then, the major types of battery modeling along with traditional battery charging and optimization techniques are presented with necessary equations and simulation proofs. The practical results implemented are also presented for reference.
{"title":"An Investigation into Battery Modelling for Electric Vehicles and Applications for Electric Power Systems","authors":"S. T., C. S, Ch V N S Pavan Pusya, R. Bhuvaneswari","doi":"10.1109/ICCMC53470.2022.9753907","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753907","url":null,"abstract":"A system for battery management is vital in reliable and safe battery operation. They are being extensively applied in high power applications, hybrid electric vehicles, and many more arenas to ensure intermittent power supply. The paper aims at providing a detailed study of the different batteries available in the market and their efficacy when exposed to different environments. The main parameters taken into consideration are the service life, nominal voltage, charging and discharging rates, and temperatures. Firstly, types of battery modeling are studied comprehensively followed by various batteries used in the industry for EVs and Power system applications. Various battery models such as electrical, thermal, and coupled electrothermal model are discussed. Subsequently, the battery condition estimates for the charging state, health estimation, and internal temperature are extensively studied. Then, the major types of battery modeling along with traditional battery charging and optimization techniques are presented with necessary equations and simulation proofs. The practical results implemented are also presented for reference.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133957489","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}
The inner keyword attack happens when keywords are not entered with high entropy and meaningfulness, which leads to easy guessing and eradication of the semantic security of most keyword searching schemes. To avoid these attacks, the keyword search security mechanism known as public-key encryption and the security models are proposed. A single server does not has the competence of finding out the similarities between keywords. Henceforth, this research study analyzes how far the security models are efficiently used for searching attacks, and proposed novel security mechanisms to define all the aspects of security models and develop novel methods to avoid keyword guessing attacks.
{"title":"Dual Server Construction using Double Encryption","authors":"Swapna Yenugula, Hussain Shaik, Karthik Chithapuram, Shyam Gajam","doi":"10.1109/ICCMC53470.2022.9753771","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753771","url":null,"abstract":"The inner keyword attack happens when keywords are not entered with high entropy and meaningfulness, which leads to easy guessing and eradication of the semantic security of most keyword searching schemes. To avoid these attacks, the keyword search security mechanism known as public-key encryption and the security models are proposed. A single server does not has the competence of finding out the similarities between keywords. Henceforth, this research study analyzes how far the security models are efficiently used for searching attacks, and proposed novel security mechanisms to define all the aspects of security models and develop novel methods to avoid keyword guessing attacks.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134347868","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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