| _version_ |
1860796916198014976
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| building |
INTELEK Repository
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| collection |
Online Access
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| collectionurl |
https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2021-03-14 03:06:04
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| eventvenue |
Penang, Malaysia
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| format |
Restricted Document
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| id |
10672
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| institution |
UniSZA
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| originalfilename |
4749-01-FH03-FIK-21-51444.pdf
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| person |
Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML
like Gecko) Chrome/88.0.4324.190 Safari/537.36
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| recordtype |
oai_dc
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| resourceurl |
https://intelek.unisza.edu.my/intelek/pages/view.php?ref=10672
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| spelling |
10672 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=10672 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper application/pdf 6 1.6 Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML like Gecko) Chrome/88.0.4324.190 Safari/537.36 Skia/PDF m88 2021-03-14 03:06:04 4749-01-FH03-FIK-21-51444.pdf UniSZA Private Access An integrated model to email spam classification using an enhanced grasshopper optimization algorithm to train a multilayer perceptron neural network Email is an important communication that the Internet has made available. One of the significance is seen in the great ease in which immediate transmission of internet data is done during email transmission. This great ease emerges with a major issue which is the continuous increase in spam emails. Thus, the need for a spam email detector. The versatility and adaptability of the nature of spam influenced past innovations. However, previous techniques have been weakened. This study introduces an email detection model that is designed based on use of an improved version of the grasshopper optimization algorithm to train a Multilayer Perceptron in classifying emails as ham and spam. To validate the performance of EGOA, executed on the spam email dataset are utilized, then the performance was relatively compared with popular search algorithms. The implementation demonstrates that EGOA introduces the best results with high accuracy of up to 96.09%. 2nd International Conference on Advances in Cyber Security Penang, Malaysia
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| spellingShingle |
An integrated model to email spam classification using an enhanced grasshopper optimization algorithm to train a multilayer perceptron neural network
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| summary |
Email is an important communication that the Internet has made available. One of the significance is seen in the great ease in which immediate transmission of internet data is done during email transmission. This great ease emerges with a major issue which is the continuous increase in spam emails. Thus, the need for a spam email detector. The versatility and adaptability of the nature of spam influenced past innovations. However, previous techniques have been weakened. This study introduces an email detection model that is designed based on use of an improved version of the grasshopper optimization algorithm to train a Multilayer Perceptron in classifying emails as ham and spam. To validate the performance of EGOA, executed on the spam email dataset are utilized, then the performance was relatively compared with popular search algorithms. The implementation demonstrates that EGOA introduces the best results with high accuracy of up to 96.09%.
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| title |
An integrated model to email spam classification using an enhanced grasshopper optimization algorithm to train a multilayer perceptron neural network
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| title_full |
An integrated model to email spam classification using an enhanced grasshopper optimization algorithm to train a multilayer perceptron neural network
|
| title_fullStr |
An integrated model to email spam classification using an enhanced grasshopper optimization algorithm to train a multilayer perceptron neural network
|
| title_full_unstemmed |
An integrated model to email spam classification using an enhanced grasshopper optimization algorithm to train a multilayer perceptron neural network
|
| title_short |
An integrated model to email spam classification using an enhanced grasshopper optimization algorithm to train a multilayer perceptron neural network
|
| title_sort |
integrated model to email spam classification using an enhanced grasshopper optimization algorithm to train a multilayer perceptron neural network
|