Towards Accurate Node-Based Detection of P2P Botnets
Botnets are a serious security threat to the current Internet infrastructure. In this paper, we propose a novel direction for P2P botnet detection called node-based detection. This approach focuses on the network characteristics of individual nodes. Based on our model, we examine node’s flows and ex...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/425491 |
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| _version_ | 1832559904158646272 |
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| author | Chunyong Yin |
| author_facet | Chunyong Yin |
| author_sort | Chunyong Yin |
| collection | DOAJ |
| description | Botnets are a serious security threat to the current Internet infrastructure. In this paper, we propose a novel direction for P2P botnet detection called node-based detection. This approach focuses on the network characteristics of individual nodes. Based on our model, we examine node’s flows and extract the useful features over a given time period. We have tested our approach on real-life data sets and achieved detection rates of 99-100% and low false positives rates of 0–2%. Comparison with other similar approaches on the same data sets shows that our approach outperforms the existing approaches. |
| format | Article |
| id | doaj-art-769d24b6bb1440c1a87058354f03f1b8 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-769d24b6bb1440c1a87058354f03f1b82025-02-03T01:28:51ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/425491425491Towards Accurate Node-Based Detection of P2P BotnetsChunyong Yin0School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaBotnets are a serious security threat to the current Internet infrastructure. In this paper, we propose a novel direction for P2P botnet detection called node-based detection. This approach focuses on the network characteristics of individual nodes. Based on our model, we examine node’s flows and extract the useful features over a given time period. We have tested our approach on real-life data sets and achieved detection rates of 99-100% and low false positives rates of 0–2%. Comparison with other similar approaches on the same data sets shows that our approach outperforms the existing approaches.http://dx.doi.org/10.1155/2014/425491 |
| spellingShingle | Chunyong Yin Towards Accurate Node-Based Detection of P2P Botnets The Scientific World Journal |
| title | Towards Accurate Node-Based Detection of P2P Botnets |
| title_full | Towards Accurate Node-Based Detection of P2P Botnets |
| title_fullStr | Towards Accurate Node-Based Detection of P2P Botnets |
| title_full_unstemmed | Towards Accurate Node-Based Detection of P2P Botnets |
| title_short | Towards Accurate Node-Based Detection of P2P Botnets |
| title_sort | towards accurate node based detection of p2p botnets |
| url | http://dx.doi.org/10.1155/2014/425491 |
| work_keys_str_mv | AT chunyongyin towardsaccuratenodebaseddetectionofp2pbotnets |