Attopo: An SDN Non-Protocol Topology Discovery Method Based on Attention Mechanism and Network Flow Analysis
In an SDN environment, topology discovery is a key function that allows the network controller to accurately understand how network devices are connected and interact. Traditional topology discovery methods typically rely on specific protocols, such as LLDP (Link Layer Discovery Protocol), but these...
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10559485/ |
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| author | Tianyi Zhang Yong Wang |
| author_facet | Tianyi Zhang Yong Wang |
| author_sort | Tianyi Zhang |
| collection | DOAJ |
| description | In an SDN environment, topology discovery is a key function that allows the network controller to accurately understand how network devices are connected and interact. Traditional topology discovery methods typically rely on specific protocols, such as LLDP (Link Layer Discovery Protocol), but these methods may have issues like inefficiency and security vulnerabilities. Therefore, researchers and engineers have been exploring more secure and efficient topology discovery methods to adapt to the evolving network demands and challenges. This paper introduces a novel SDN topology discovery method, Attopo, based on the attention mechanism and network flow analysis, independent of traditional protocols. We apply the attention mechanism to SDN topology discovery for the first time and address the security vulnerabilities of the OFDP protocol through a non-protocol mechanism. Attopo combines Self-attention, Cross-attention, and Prob-attention mechanisms to analyze network flows received by the controller and extract topology information, thereby enhancing the model’s accuracy and efficiency in network topology discovery. Additionally, we have collected a dataset containing network flows and topology labels by simulating different network environments, which enhances the model’s adaptability. Experimental validation shows that our method performs well in terms of accuracy, recall rate, F1 score, and AUC metrics in topology discovery. |
| format | Article |
| id | doaj-art-abc5d68b136e44c2bea161dee25cce47 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-abc5d68b136e44c2bea161dee25cce472025-08-20T02:48:46ZengIEEEIEEE Access2169-35362024-01-011218219018220210.1109/ACCESS.2024.341538410559485Attopo: An SDN Non-Protocol Topology Discovery Method Based on Attention Mechanism and Network Flow AnalysisTianyi Zhang0https://orcid.org/0009-0004-2311-469XYong Wang1https://orcid.org/0000-0002-5383-5736School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, ChinaSchool of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, ChinaIn an SDN environment, topology discovery is a key function that allows the network controller to accurately understand how network devices are connected and interact. Traditional topology discovery methods typically rely on specific protocols, such as LLDP (Link Layer Discovery Protocol), but these methods may have issues like inefficiency and security vulnerabilities. Therefore, researchers and engineers have been exploring more secure and efficient topology discovery methods to adapt to the evolving network demands and challenges. This paper introduces a novel SDN topology discovery method, Attopo, based on the attention mechanism and network flow analysis, independent of traditional protocols. We apply the attention mechanism to SDN topology discovery for the first time and address the security vulnerabilities of the OFDP protocol through a non-protocol mechanism. Attopo combines Self-attention, Cross-attention, and Prob-attention mechanisms to analyze network flows received by the controller and extract topology information, thereby enhancing the model’s accuracy and efficiency in network topology discovery. Additionally, we have collected a dataset containing network flows and topology labels by simulating different network environments, which enhances the model’s adaptability. Experimental validation shows that our method performs well in terms of accuracy, recall rate, F1 score, and AUC metrics in topology discovery.https://ieeexplore.ieee.org/document/10559485/SDNtopology discoveryattention mechanismnon-protocol methodnetwork flow analysis |
| spellingShingle | Tianyi Zhang Yong Wang Attopo: An SDN Non-Protocol Topology Discovery Method Based on Attention Mechanism and Network Flow Analysis IEEE Access SDN topology discovery attention mechanism non-protocol method network flow analysis |
| title | Attopo: An SDN Non-Protocol Topology Discovery Method Based on Attention Mechanism and Network Flow Analysis |
| title_full | Attopo: An SDN Non-Protocol Topology Discovery Method Based on Attention Mechanism and Network Flow Analysis |
| title_fullStr | Attopo: An SDN Non-Protocol Topology Discovery Method Based on Attention Mechanism and Network Flow Analysis |
| title_full_unstemmed | Attopo: An SDN Non-Protocol Topology Discovery Method Based on Attention Mechanism and Network Flow Analysis |
| title_short | Attopo: An SDN Non-Protocol Topology Discovery Method Based on Attention Mechanism and Network Flow Analysis |
| title_sort | attopo an sdn non protocol topology discovery method based on attention mechanism and network flow analysis |
| topic | SDN topology discovery attention mechanism non-protocol method network flow analysis |
| url | https://ieeexplore.ieee.org/document/10559485/ |
| work_keys_str_mv | AT tianyizhang attopoansdnnonprotocoltopologydiscoverymethodbasedonattentionmechanismandnetworkflowanalysis AT yongwang attopoansdnnonprotocoltopologydiscoverymethodbasedonattentionmechanismandnetworkflowanalysis |