Research on structure and defense of adversarial example in deep learning
With the further promotion of deep learning technology in the fields of computer vision,network security and natural language processing,which has gradually exposed certain security risks.Existing deep learning algorithms can not effectively describe the essential characteristics of data or its inhe...
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| Format: | Article |
| Language: | English |
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POSTS&TELECOM PRESS Co., LTD
2020-04-01
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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.2020016 |
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| _version_ | 1841529936790159360 |
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| author | Guanghan DUAN Chunguang MA Lei SONG Peng WU |
| author_facet | Guanghan DUAN Chunguang MA Lei SONG Peng WU |
| author_sort | Guanghan DUAN |
| collection | DOAJ |
| description | With the further promotion of deep learning technology in the fields of computer vision,network security and natural language processing,which has gradually exposed certain security risks.Existing deep learning algorithms can not effectively describe the essential characteristics of data or its inherent causal relationship.When the algorithm faces malicious input,it often fails to give correct judgment results.Based on the current security threats of deep learning,the adversarial example problem and its characteristics in deep learning applications were introduced,hypotheses on the existence of adversarial examples were summarized,classic adversarial example construction methods were reviewed and recent research status in different scenarios were summarized,several defense techniques in different processes were compared,and finally the development trend of adversarial example research were forecasted. |
| format | Article |
| id | doaj-art-06f1b5ec000849e3818a790636c1dd96 |
| institution | Kabale University |
| issn | 2096-109X |
| language | English |
| publishDate | 2020-04-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 网络与信息安全学报 |
| spelling | doaj-art-06f1b5ec000849e3818a790636c1dd962025-01-15T03:13:58ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2020-04-01611159558225Research on structure and defense of adversarial example in deep learningGuanghan DUANChunguang MALei SONGPeng WUWith the further promotion of deep learning technology in the fields of computer vision,network security and natural language processing,which has gradually exposed certain security risks.Existing deep learning algorithms can not effectively describe the essential characteristics of data or its inherent causal relationship.When the algorithm faces malicious input,it often fails to give correct judgment results.Based on the current security threats of deep learning,the adversarial example problem and its characteristics in deep learning applications were introduced,hypotheses on the existence of adversarial examples were summarized,classic adversarial example construction methods were reviewed and recent research status in different scenarios were summarized,several defense techniques in different processes were compared,and finally the development trend of adversarial example research were forecasted.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020016adversarial exampledeep learningsecurity threatdefense technology |
| spellingShingle | Guanghan DUAN Chunguang MA Lei SONG Peng WU Research on structure and defense of adversarial example in deep learning 网络与信息安全学报 adversarial example deep learning security threat defense technology |
| title | Research on structure and defense of adversarial example in deep learning |
| title_full | Research on structure and defense of adversarial example in deep learning |
| title_fullStr | Research on structure and defense of adversarial example in deep learning |
| title_full_unstemmed | Research on structure and defense of adversarial example in deep learning |
| title_short | Research on structure and defense of adversarial example in deep learning |
| title_sort | research on structure and defense of adversarial example in deep learning |
| topic | adversarial example deep learning security threat defense technology |
| url | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020016 |
| work_keys_str_mv | AT guanghanduan researchonstructureanddefenseofadversarialexampleindeeplearning AT chunguangma researchonstructureanddefenseofadversarialexampleindeeplearning AT leisong researchonstructureanddefenseofadversarialexampleindeeplearning AT pengwu researchonstructureanddefenseofadversarialexampleindeeplearning |