Study of SDN intrusion intent identification algorithm based on Bayesian attack graph
Since the existing software defined network (SDN) security prediction methods do not consider the attack cost and the impact of controller vulnerabilities on SDN security, a Bayesian attack graph-based algorithm to assessing SDN intrusion intent was proposed.The PageRank algorithm was used to obtain...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2023-04-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023073/ |
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| _version_ | 1841539961802719232 |
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| author | Zhiyong LUO Yu ZHANG Qing WANG Weiwei SONG |
| author_facet | Zhiyong LUO Yu ZHANG Qing WANG Weiwei SONG |
| author_sort | Zhiyong LUO |
| collection | DOAJ |
| description | Since the existing software defined network (SDN) security prediction methods do not consider the attack cost and the impact of controller vulnerabilities on SDN security, a Bayesian attack graph-based algorithm to assessing SDN intrusion intent was proposed.The PageRank algorithm was used to obtain the criticality of the device, and combining with the vulnerability value, attack cost, attack benefit and attack preference, an attack graph was constructed, and a risk assessment model was established to predict the intrusion path.Through experimental comparison, it is obvious that the proposed model can more accurately predict the intrusion path, effectively ensure the accuracy of security prediction, and provide a basis for SDN defense. |
| format | Article |
| id | doaj-art-2de0a719bcc5489d9fc1f9ba2804c80d |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2023-04-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-2de0a719bcc5489d9fc1f9ba2804c80d2025-01-14T06:28:31ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2023-04-014421622559390561Study of SDN intrusion intent identification algorithm based on Bayesian attack graphZhiyong LUOYu ZHANGQing WANGWeiwei SONGSince the existing software defined network (SDN) security prediction methods do not consider the attack cost and the impact of controller vulnerabilities on SDN security, a Bayesian attack graph-based algorithm to assessing SDN intrusion intent was proposed.The PageRank algorithm was used to obtain the criticality of the device, and combining with the vulnerability value, attack cost, attack benefit and attack preference, an attack graph was constructed, and a risk assessment model was established to predict the intrusion path.Through experimental comparison, it is obvious that the proposed model can more accurately predict the intrusion path, effectively ensure the accuracy of security prediction, and provide a basis for SDN defense.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023073/SDN security predictionintrusion intentionattack graphPageRank algorithm |
| spellingShingle | Zhiyong LUO Yu ZHANG Qing WANG Weiwei SONG Study of SDN intrusion intent identification algorithm based on Bayesian attack graph Tongxin xuebao SDN security prediction intrusion intention attack graph PageRank algorithm |
| title | Study of SDN intrusion intent identification algorithm based on Bayesian attack graph |
| title_full | Study of SDN intrusion intent identification algorithm based on Bayesian attack graph |
| title_fullStr | Study of SDN intrusion intent identification algorithm based on Bayesian attack graph |
| title_full_unstemmed | Study of SDN intrusion intent identification algorithm based on Bayesian attack graph |
| title_short | Study of SDN intrusion intent identification algorithm based on Bayesian attack graph |
| title_sort | study of sdn intrusion intent identification algorithm based on bayesian attack graph |
| topic | SDN security prediction intrusion intention attack graph PageRank algorithm |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023073/ |
| work_keys_str_mv | AT zhiyongluo studyofsdnintrusionintentidentificationalgorithmbasedonbayesianattackgraph AT yuzhang studyofsdnintrusionintentidentificationalgorithmbasedonbayesianattackgraph AT qingwang studyofsdnintrusionintentidentificationalgorithmbasedonbayesianattackgraph AT weiweisong studyofsdnintrusionintentidentificationalgorithmbasedonbayesianattackgraph |