Research on discovering multi-step attack patterns based on clustering IDS alert sequences
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Research on discovering multi-step attack patterns based on clustering IDS alert sequences
Vol. 32, Issue 5, Pages: 63-69(2011)
作者机构:
1. 东南大学计算机科学与工程学院江苏省计算机网络技术重点实验室
2. 上海海洋大学信息学院
作者简介:
基金信息:
DOI:
CLC:TP393.08
Published:2011
稿件说明:
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MEI Hai-bin1, GONG Jian1, ZHANG Ming-hua2. Research on discovering multi-step attack patterns based on clustering IDS alert sequences[J]. 2011, 32(5): 63-69.
DOI:
MEI Hai-bin1, GONG Jian1, ZHANG Ming-hua2. Research on discovering multi-step attack patterns based on clustering IDS alert sequences[J]. 2011, 32(5): 63-69.DOI:
Research on discovering multi-step attack patterns based on clustering IDS alert sequences
A method of discovering multi-step attack patterns from alert data was studied.Alert similarity function was defined to construct the set of attack activity sequences.Sequence alignment technology was used to cluster the similar attack activity sequences.Multi-step attack patterns in a cluster were automatically discovered by the longest common subsequence extraction algorithm based on the idea of dynamic programming.The proposed method didn’t depend on large amounts of prior knowledge.Few configuration parameters were needed and it was easy to implement.Experimental results demonstrate the effectiveness of proposed method.