Physical-social attributes integrated Sybil detection for Tor bridge distribution
As one of the most widely utilized censorship circumvention systems, Tor faces serious Sybil attacks in bridge distribution.Censors with rich network and human resources usually deploy a large number of Sybils, which disguise themselves as normal nodes to obtain bridges information and block them.In...
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| Format: | Article |
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POSTS&TELECOM PRESS Co., LTD
2023-02-01
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| Series: | 网络与信息安全学报 |
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| Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2023014 |
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| _version_ | 1841529605145493504 |
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| author | Xin SHI Yunfei GUO Yawen WANG Xiaoli SUN Hao LIANG |
| author_facet | Xin SHI Yunfei GUO Yawen WANG Xiaoli SUN Hao LIANG |
| author_sort | Xin SHI |
| collection | DOAJ |
| description | As one of the most widely utilized censorship circumvention systems, Tor faces serious Sybil attacks in bridge distribution.Censors with rich network and human resources usually deploy a large number of Sybils, which disguise themselves as normal nodes to obtain bridges information and block them.In the process, due to the different identities, purposes and intentions of Sybils and normal nodes, individual or group behavior differences occur in network activities, called as node behavior characteristics.To handle the Sybil attacks threat, a Sybil detection mechanism integrating physical-social attributes was proposed based on the analysis of node behavior characteristics.The physical-social attributes evaluation methods were designed.The credit value of nodes objectively reflecting the operation status of bridges on the nodes and the suspicion index of nodes reflecting the blocking status of bridges, were utilized to evaluate the physical attributes of nodes.The social attributes of nodes were evaluated by the social similarity, which described the static attribute labels of nodes and their social trust characterizing the dynamic interaction behaviors of nodes.Furthermore, integrating the physical-social attributes, the credibility of nodes were defined as the possibility of the current node being a Sybil, which was exploited as a guidance on inferring the true identifies of nodes, so as to achieve accurate detection on Sybils.The detection performance of the proposed mechanism based on the constructed Tor network operation status simulator and the Microblog PCU dataset were simulated.The results show that the proposed mechanism can effectively improve the true positive rate on Sybils, and decrease the false positive rate.It also has stronger resistance on the deceptive behavior of censors, and still performs well in the absence of node social attributes. |
| format | Article |
| id | doaj-art-4df099d145144fca96b4c307533e2187 |
| institution | Kabale University |
| issn | 2096-109X |
| language | English |
| publishDate | 2023-02-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 网络与信息安全学报 |
| spelling | doaj-art-4df099d145144fca96b4c307533e21872025-01-15T03:16:29ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2023-02-01910311459577286Physical-social attributes integrated Sybil detection for Tor bridge distributionXin SHIYunfei GUOYawen WANGXiaoli SUNHao LIANGAs one of the most widely utilized censorship circumvention systems, Tor faces serious Sybil attacks in bridge distribution.Censors with rich network and human resources usually deploy a large number of Sybils, which disguise themselves as normal nodes to obtain bridges information and block them.In the process, due to the different identities, purposes and intentions of Sybils and normal nodes, individual or group behavior differences occur in network activities, called as node behavior characteristics.To handle the Sybil attacks threat, a Sybil detection mechanism integrating physical-social attributes was proposed based on the analysis of node behavior characteristics.The physical-social attributes evaluation methods were designed.The credit value of nodes objectively reflecting the operation status of bridges on the nodes and the suspicion index of nodes reflecting the blocking status of bridges, were utilized to evaluate the physical attributes of nodes.The social attributes of nodes were evaluated by the social similarity, which described the static attribute labels of nodes and their social trust characterizing the dynamic interaction behaviors of nodes.Furthermore, integrating the physical-social attributes, the credibility of nodes were defined as the possibility of the current node being a Sybil, which was exploited as a guidance on inferring the true identifies of nodes, so as to achieve accurate detection on Sybils.The detection performance of the proposed mechanism based on the constructed Tor network operation status simulator and the Microblog PCU dataset were simulated.The results show that the proposed mechanism can effectively improve the true positive rate on Sybils, and decrease the false positive rate.It also has stronger resistance on the deceptive behavior of censors, and still performs well in the absence of node social attributes.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2023014Tor bridge distributionSybil detectionbehavior characteristicsphysical-social attributes |
| spellingShingle | Xin SHI Yunfei GUO Yawen WANG Xiaoli SUN Hao LIANG Physical-social attributes integrated Sybil detection for Tor bridge distribution 网络与信息安全学报 Tor bridge distribution Sybil detection behavior characteristics physical-social attributes |
| title | Physical-social attributes integrated Sybil detection for Tor bridge distribution |
| title_full | Physical-social attributes integrated Sybil detection for Tor bridge distribution |
| title_fullStr | Physical-social attributes integrated Sybil detection for Tor bridge distribution |
| title_full_unstemmed | Physical-social attributes integrated Sybil detection for Tor bridge distribution |
| title_short | Physical-social attributes integrated Sybil detection for Tor bridge distribution |
| title_sort | physical social attributes integrated sybil detection for tor bridge distribution |
| topic | Tor bridge distribution Sybil detection behavior characteristics physical-social attributes |
| url | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2023014 |
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