Attention-based approach of detecting spam in social networks
In social networks,a large amount of spam has seriously threaten users' information security and the credit system of social websites.Aiming at the noise and sparsity problems,an attention-based CNN method was proposed to detect spam.On the basis of classical CNN,this method added a filter laye...
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| Format: | Article |
| Language: | English |
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POSTS&TELECOM PRESS Co., LTD
2020-02-01
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| Series: | 网络与信息安全学报 |
| Subjects: | |
| Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020002 |
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| _version_ | 1841529992229421056 |
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| author | Qiang QU Hongtao YU Ruiyang HUANG |
| author_facet | Qiang QU Hongtao YU Ruiyang HUANG |
| author_sort | Qiang QU |
| collection | DOAJ |
| description | In social networks,a large amount of spam has seriously threaten users' information security and the credit system of social websites.Aiming at the noise and sparsity problems,an attention-based CNN method was proposed to detect spam.On the basis of classical CNN,this method added a filter layer in which an attention mechanism based on Naive Bayesian weighting technology was designed to solve the noise issue.What’s more,instead of the original pooling strategy,it adapted an attention-based pooling policy to alleviate the sparsity problem.Compared with other methods,the results show that the accuracy has increased by 1.32%，2.15%，0.07%，1.63% on four different data sets. |
| format | Article |
| id | doaj-art-a737cf6753104ebfb4d9b33895d6bd60 |
| institution | Kabale University |
| issn | 2096-109X |
| language | English |
| publishDate | 2020-02-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 网络与信息安全学报 |
| spelling | doaj-art-a737cf6753104ebfb4d9b33895d6bd602025-01-15T03:13:55ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2020-02-016546159557783Attention-based approach of detecting spam in social networksQiang QUHongtao YURuiyang HUANGIn social networks,a large amount of spam has seriously threaten users' information security and the credit system of social websites.Aiming at the noise and sparsity problems,an attention-based CNN method was proposed to detect spam.On the basis of classical CNN,this method added a filter layer in which an attention mechanism based on Naive Bayesian weighting technology was designed to solve the noise issue.What’s more,instead of the original pooling strategy,it adapted an attention-based pooling policy to alleviate the sparsity problem.Compared with other methods,the results show that the accuracy has increased by 1.32%，2.15%，0.07%，1.63% on four different data sets.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020002social networksinformation securityspamattention system |
| spellingShingle | Qiang QU Hongtao YU Ruiyang HUANG Attention-based approach of detecting spam in social networks 网络与信息安全学报 social networks information security spam attention system |
| title | Attention-based approach of detecting spam in social networks |
| title_full | Attention-based approach of detecting spam in social networks |
| title_fullStr | Attention-based approach of detecting spam in social networks |
| title_full_unstemmed | Attention-based approach of detecting spam in social networks |
| title_short | Attention-based approach of detecting spam in social networks |
| title_sort | attention based approach of detecting spam in social networks |
| topic | social networks information security spam attention system |
| url | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020002 |
| work_keys_str_mv | AT qiangqu attentionbasedapproachofdetectingspaminsocialnetworks AT hongtaoyu attentionbasedapproachofdetectingspaminsocialnetworks AT ruiyanghuang attentionbasedapproachofdetectingspaminsocialnetworks |