Pub Date : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9079973
Mohd Mursleen, Yogesh Kothyari
Now a days currently there is a lot of power consumption in data centers due to high demand in cloud services like online data storage services, software services on cloud like Google Apps, Sales force and platform as a service on cloud. Due to heavy usage of all these services over the Cloud, now a day's Data Centers are consuming a heavy amount of Energy. This heavy Energy Consumption by data centers is not only including the higher running cost of data centers but it is also effecting the environment inversely. There are basically two ways in which we can reduce energy consumption in Data Centers, first way is by minimising the parameter of data centers while the second method is by exercising an efficiently constructed asset allocation technique to get the optimal balance between energy consumption and performance of the data centers. In this paper, we are dealing with the second approach which is a software based approach i.e. designing an efficient resource allocation technique while the first approach is a hardware based approach. Furthermore, here we will not only deal with homogeneous data centers but we are also considering the heterogeneous data centers. So, our prime focus of this research work is to allocate the resources in homogeneous and heterogeneous data centers in such a manner that energy consumed by data centers usage becomes optimal and energy consumption is reduced without effecting in the performance of data centers. Therefore, for the above we have come up with a novel algorithm toward energy efficiency in such a way that it takes care of scheduling the algorithm fairly while allocating the resources of data centers.
{"title":"An Energy-Efficient Allocation Technique for Distributing Resources in a Heterogeneous Data Center","authors":"Mohd Mursleen, Yogesh Kothyari","doi":"10.1109/ICACCE46606.2019.9079973","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079973","url":null,"abstract":"Now a days currently there is a lot of power consumption in data centers due to high demand in cloud services like online data storage services, software services on cloud like Google Apps, Sales force and platform as a service on cloud. Due to heavy usage of all these services over the Cloud, now a day's Data Centers are consuming a heavy amount of Energy. This heavy Energy Consumption by data centers is not only including the higher running cost of data centers but it is also effecting the environment inversely. There are basically two ways in which we can reduce energy consumption in Data Centers, first way is by minimising the parameter of data centers while the second method is by exercising an efficiently constructed asset allocation technique to get the optimal balance between energy consumption and performance of the data centers. In this paper, we are dealing with the second approach which is a software based approach i.e. designing an efficient resource allocation technique while the first approach is a hardware based approach. Furthermore, here we will not only deal with homogeneous data centers but we are also considering the heterogeneous data centers. So, our prime focus of this research work is to allocate the resources in homogeneous and heterogeneous data centers in such a manner that energy consumed by data centers usage becomes optimal and energy consumption is reduced without effecting in the performance of data centers. Therefore, for the above we have come up with a novel algorithm toward energy efficiency in such a way that it takes care of scheduling the algorithm fairly while allocating the resources of data centers.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126451272","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9079993
T. Prasanth, K. Aarthi, M. Gunasekaran
Any type of organization depends on accurate data analytics to make better decisions. Users of these organizations request access from different resources like processes or executors. When processing this request of users, the data retrieval speed is low and also data is inaccurate for some conditions. To solve this issue, a system may be proposed having Hadoop Distributed File system (HDFS) with Lempel-Ziv-Oberhumer(LZO). The first step in the proposed technique is to retrieve and mine the data from respective database. The next step is to cluster the extracted data and optimize it using HDFS and LZO compression method. In the last step, if the compressed data is found similar to user requested data, the final data has to be visualized to the user. The proposed retrieving process in big data gives better performance and reduced execution time.
{"title":"Big Data Retrieval using HDFS with LZO Compression","authors":"T. Prasanth, K. Aarthi, M. Gunasekaran","doi":"10.1109/ICACCE46606.2019.9079993","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079993","url":null,"abstract":"Any type of organization depends on accurate data analytics to make better decisions. Users of these organizations request access from different resources like processes or executors. When processing this request of users, the data retrieval speed is low and also data is inaccurate for some conditions. To solve this issue, a system may be proposed having Hadoop Distributed File system (HDFS) with Lempel-Ziv-Oberhumer(LZO). The first step in the proposed technique is to retrieve and mine the data from respective database. The next step is to cluster the extracted data and optimize it using HDFS and LZO compression method. In the last step, if the compressed data is found similar to user requested data, the final data has to be visualized to the user. The proposed retrieving process in big data gives better performance and reduced execution time.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114267978","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9079971
K. Nirmalakumari, H. Rajaguru, P. Rajkumar
Recognition of human fingerprint verifies the match among two fingerprints in an automatic way and it is applied in various fields. The fingerprints are unique and its pattern will remain the same for the lifetime. The minutiae points represent the features of fingerprint that aids in the authentication of fingerprints. The main aim of this paper is to improve a scheme for verification of fingerprint by means of feature extraction and matching techniques. The initial step is preprocessing that involves image enhancement and binarization processes for the poor quality input fingerprint images. The fingerprint verification involves two main steps namely minutiae extraction and minutiae matching. The false minutiae points are to be removed and only efficient minutiae points are to be considered for further process. In this work, two publically available fingerprint datasets are utilized and the accuracy of fingerprint recognition is evaluated using the performance measures namely False Matching Ratio (FMR), False Non Matching Ratio (FNMR) and Threshold. From the results, it is clear that our work provides better results in fingerprint recognition.
{"title":"Efficient Minutiae Matching Algorithm for Fingerprint Recognition","authors":"K. Nirmalakumari, H. Rajaguru, P. Rajkumar","doi":"10.1109/ICACCE46606.2019.9079971","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079971","url":null,"abstract":"Recognition of human fingerprint verifies the match among two fingerprints in an automatic way and it is applied in various fields. The fingerprints are unique and its pattern will remain the same for the lifetime. The minutiae points represent the features of fingerprint that aids in the authentication of fingerprints. The main aim of this paper is to improve a scheme for verification of fingerprint by means of feature extraction and matching techniques. The initial step is preprocessing that involves image enhancement and binarization processes for the poor quality input fingerprint images. The fingerprint verification involves two main steps namely minutiae extraction and minutiae matching. The false minutiae points are to be removed and only efficient minutiae points are to be considered for further process. In this work, two publically available fingerprint datasets are utilized and the accuracy of fingerprint recognition is evaluated using the performance measures namely False Matching Ratio (FMR), False Non Matching Ratio (FNMR) and Threshold. From the results, it is clear that our work provides better results in fingerprint recognition.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114413520","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9079966
P. Kathirvel, P. Parthiban
An Indian thermal power heavy industry has to focus more on sustainable supply chain activities. To increase the sustainable recitation of a supply chain, the SSCM experts should select their suppliers prudently in relation to their own stratagem. Sustainability supply chain management can be maintained by reducing the influence of the barriers of Economic stability, Social Ethics, and Environmental Conservation. These three factors are called the Triple Bottom Line (TBL) concept of the sustainable supply chain management. The factor is considered from the previous research and the team of experts evaluate the factors and factors are given weights accordingly. The barriers of the economic social and environmental are the cost of implementation, lack of potential to save money, Infrastructure, Absence of incentive policies and lack of preparation, understanding & knowledge, Organizational culture also lack awareness of existing environmental regulations, expertise, and understanding of strategies to address environmental issues etc. This research helps to assess an assortment of the suppliers of the thermal power heavy industry based on their performance of The MCDM tool TOPSIS is used to rank the suppliers in thermal power heavy industry. The research also developing healthy competition among the suppliers and improving performance.
{"title":"Supplier Management and Selection System considering Sustainability for a Thermal Power Heavy Industry","authors":"P. Kathirvel, P. Parthiban","doi":"10.1109/ICACCE46606.2019.9079966","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079966","url":null,"abstract":"An Indian thermal power heavy industry has to focus more on sustainable supply chain activities. To increase the sustainable recitation of a supply chain, the SSCM experts should select their suppliers prudently in relation to their own stratagem. Sustainability supply chain management can be maintained by reducing the influence of the barriers of Economic stability, Social Ethics, and Environmental Conservation. These three factors are called the Triple Bottom Line (TBL) concept of the sustainable supply chain management. The factor is considered from the previous research and the team of experts evaluate the factors and factors are given weights accordingly. The barriers of the economic social and environmental are the cost of implementation, lack of potential to save money, Infrastructure, Absence of incentive policies and lack of preparation, understanding & knowledge, Organizational culture also lack awareness of existing environmental regulations, expertise, and understanding of strategies to address environmental issues etc. This research helps to assess an assortment of the suppliers of the thermal power heavy industry based on their performance of The MCDM tool TOPSIS is used to rank the suppliers in thermal power heavy industry. The research also developing healthy competition among the suppliers and improving performance.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132544863","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9079982
J. Lakshmi, N. Shankar, K. Maheswari, S. Manivannan
Solar energy is the most popular renewable energy source in the recent times. The use of solar energy for electricity generation is limited and it's non- continuous availability makes the solar power unreliable for critical applications. These problems can be overcome by using other resources in parallel with the solar energy and making it to operate when the solar power is not available. One such solution includes the usage of Hybrid Energy Storage System along with solar power. HESS has different configurations and includes different resources. Here the battery is used as a backup source along with solar. The battery gets charged during the time when solar power is available and the load is supplied by the battery storage while the solar power is unavailable. This system is discussed in detail in this paper. The power flow in both the direction will be controlled by the bidirectional converter. This paper also discusses the simulated results of this proposed system in detail.
{"title":"Improved Bidirectional Converter for PV System with Battery Storage","authors":"J. Lakshmi, N. Shankar, K. Maheswari, S. Manivannan","doi":"10.1109/ICACCE46606.2019.9079982","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079982","url":null,"abstract":"Solar energy is the most popular renewable energy source in the recent times. The use of solar energy for electricity generation is limited and it's non- continuous availability makes the solar power unreliable for critical applications. These problems can be overcome by using other resources in parallel with the solar energy and making it to operate when the solar power is not available. One such solution includes the usage of Hybrid Energy Storage System along with solar power. HESS has different configurations and includes different resources. Here the battery is used as a backup source along with solar. The battery gets charged during the time when solar power is available and the load is supplied by the battery storage while the solar power is unavailable. This system is discussed in detail in this paper. The power flow in both the direction will be controlled by the bidirectional converter. This paper also discusses the simulated results of this proposed system in detail.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129198056","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9079963
B. Hemalatha, S. Yuvaraj, K. Kiruthikaa, V. Viswanathan
The main source of lung cancer is to gasping the tobacco smoke regularly, which affects around 90% of lung cancers. Cancer cells are to be carried to and from the lungs within the blood or lymph fluid ambience the lung tissue. Early diagnosis and treatment can save life. In this, the image processing techniques have been utilized to identify the lung cancer. Initially, the CT scan image is pre-processed for removing the unwanted signals and smoothing them by employing Improved Kaun Filter (IKF). Subsequently, the preprocessed image is portioned by an Active contour method to get exactness of segmented results. Next, specific features are extracted to raise the anticipated accuracy. At last, the tumour has been categorized by Elman Neural Network (ENN) and weights are optimized with PSO and compared the accuracy results with SVM, RBFN and ANFIS.
{"title":"Automatic Detection of Lung Cancer Identification using ENNPSO Classification","authors":"B. Hemalatha, S. Yuvaraj, K. Kiruthikaa, V. Viswanathan","doi":"10.1109/ICACCE46606.2019.9079963","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079963","url":null,"abstract":"The main source of lung cancer is to gasping the tobacco smoke regularly, which affects around 90% of lung cancers. Cancer cells are to be carried to and from the lungs within the blood or lymph fluid ambience the lung tissue. Early diagnosis and treatment can save life. In this, the image processing techniques have been utilized to identify the lung cancer. Initially, the CT scan image is pre-processed for removing the unwanted signals and smoothing them by employing Improved Kaun Filter (IKF). Subsequently, the preprocessed image is portioned by an Active contour method to get exactness of segmented results. Next, specific features are extracted to raise the anticipated accuracy. At last, the tumour has been categorized by Elman Neural Network (ENN) and weights are optimized with PSO and compared the accuracy results with SVM, RBFN and ANFIS.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116373108","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9079995
T. Ananda, Gitanjali Simran T, S. T, S. D, R. P.
With the technological explosion of Internet of Things(IoT) and the conception of every particle being tied to the Internet, the “security” of these globally connected nodes is critical. The availability and reliability of these networked nodes can be guaranteed by securing the physical nodes and the data associated with them but more importantly by ensuring the network security associated with their communication stack. Thus, in this paper we evaluate the security robustness of the Network protocols associated with these networking capable devices through Fuzzing or corner case checks. Through the Fuzz assessments, we can assess the node behavior when the various applications are under fuzz and establish the security damage/robustness associated with it. This supplies a point of node vulnerability to be fixed before the node connects with a global network.
{"title":"Robustness Evaluation of Cyber Physical Systems through Network Protocol Fuzzing","authors":"T. Ananda, Gitanjali Simran T, S. T, S. D, R. P.","doi":"10.1109/ICACCE46606.2019.9079995","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079995","url":null,"abstract":"With the technological explosion of Internet of Things(IoT) and the conception of every particle being tied to the Internet, the “security” of these globally connected nodes is critical. The availability and reliability of these networked nodes can be guaranteed by securing the physical nodes and the data associated with them but more importantly by ensuring the network security associated with their communication stack. Thus, in this paper we evaluate the security robustness of the Network protocols associated with these networking capable devices through Fuzzing or corner case checks. Through the Fuzz assessments, we can assess the node behavior when the various applications are under fuzz and establish the security damage/robustness associated with it. This supplies a point of node vulnerability to be fixed before the node connects with a global network.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114357215","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9080001
P. Vanitha, Sreejith Alathur
Electronic learning is a formalized teaching-learning service using electronic resources. With the help of Information and Communication Technologies (ICTs), knowledge can be shared via the Internet anywhere, anytime. Although, the massive growth of technologies available, e-learning service may not distribute equally in developing countries like India. The objective of the study is to explore the technological challenges of e-learning services in the Indian context. In the present study, the real-time feedback about the technological challenges is collected directly from Twitter social media. Initially, the tweets were extracted based on the hashtags, and the location-based analysis is performed using geocoding. In this study, various types of technological challenges are identified, and the most influential factor is determined. It gives better results when this research is carried on developing countries like India. The suggestion provided in this research will help to decrease the technological challenges in the e-learning service.
{"title":"E-learning services: Insights from Twitter Analytics","authors":"P. Vanitha, Sreejith Alathur","doi":"10.1109/ICACCE46606.2019.9080001","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9080001","url":null,"abstract":"Electronic learning is a formalized teaching-learning service using electronic resources. With the help of Information and Communication Technologies (ICTs), knowledge can be shared via the Internet anywhere, anytime. Although, the massive growth of technologies available, e-learning service may not distribute equally in developing countries like India. The objective of the study is to explore the technological challenges of e-learning services in the Indian context. In the present study, the real-time feedback about the technological challenges is collected directly from Twitter social media. Initially, the tweets were extracted based on the hashtags, and the location-based analysis is performed using geocoding. In this study, various types of technological challenges are identified, and the most influential factor is determined. It gives better results when this research is carried on developing countries like India. The suggestion provided in this research will help to decrease the technological challenges in the e-learning service.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121931085","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9079952
Naganna Chetty, Sreejith Alathur
The problematic act damages the target and seeds the fear in the neighborhood. Social media sites are used for planning and coordinating problematic acts. The problematic act is a trigger event which influences hatred feeling. The objective of the paper is to analyze the aftermath of a recent problematic incident in the southern part of the Asian continent from Twitter content. After the problematic incident, citizens used to share their views over social media sites. A total of 48,819 opinions shared through Twitter social media are collected and analyzed using the software developed in the R programming language. The results show hatred against the problematic act through different related emotions. Results also contain more negative tweets which are almost thrice the positive tweets. Fear and anger emotions exhibit a high degree of emotions than the other.
{"title":"Trigger Event and Hate Content: Insights from Twitter Analytics","authors":"Naganna Chetty, Sreejith Alathur","doi":"10.1109/ICACCE46606.2019.9079952","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079952","url":null,"abstract":"The problematic act damages the target and seeds the fear in the neighborhood. Social media sites are used for planning and coordinating problematic acts. The problematic act is a trigger event which influences hatred feeling. The objective of the paper is to analyze the aftermath of a recent problematic incident in the southern part of the Asian continent from Twitter content. After the problematic incident, citizens used to share their views over social media sites. A total of 48,819 opinions shared through Twitter social media are collected and analyzed using the software developed in the R programming language. The results show hatred against the problematic act through different related emotions. Results also contain more negative tweets which are almost thrice the positive tweets. Fear and anger emotions exhibit a high degree of emotions than the other.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132773171","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9080000
V. Vinitha, D. Renuka
Most of the business and general communication is done through email because of its cost effectiveness. This efficiency leads email exposed to various attacks including spamming. Nowadays spam email is the foremost concern for email users. These spams are used for sending fake proposals, advertisements, and harmful contents in the form of executable file to attack user systems or the link to the malicious websites resulting in the unessential consumption of network bandwidth. This paper elucidates the different Machine Learning Techniques such as J48 classifier, Adaboost, K-Nearest Neighbor, Naive Bayes, Artificial Neural Network, Support Vector Machine, and Random Forests algorithm for filtering spam emails using different email dataset. However, here the comparison of different spam email classification technique is presented and summarizes the overall scenario regarding accuracy rate of different existing approaches.
{"title":"Performance Analysis of E-Mail Spam Classification using different Machine Learning Techniques","authors":"V. Vinitha, D. Renuka","doi":"10.1109/ICACCE46606.2019.9080000","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9080000","url":null,"abstract":"Most of the business and general communication is done through email because of its cost effectiveness. This efficiency leads email exposed to various attacks including spamming. Nowadays spam email is the foremost concern for email users. These spams are used for sending fake proposals, advertisements, and harmful contents in the form of executable file to attack user systems or the link to the malicious websites resulting in the unessential consumption of network bandwidth. This paper elucidates the different Machine Learning Techniques such as J48 classifier, Adaboost, K-Nearest Neighbor, Naive Bayes, Artificial Neural Network, Support Vector Machine, and Random Forests algorithm for filtering spam emails using different email dataset. However, here the comparison of different spam email classification technique is presented and summarizes the overall scenario regarding accuracy rate of different existing approaches.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134398170","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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