Reducing false positives of network anomaly detection by local adaptive multivariate smoothing
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- 作者：Martin Grilla ; b ; magrill@cisco.com" class="auth_mail" title="E-mail the corresponding author ; Tomá ; &scaron ; Pevný ; a ; b ; tpevny@cisco.com" class="auth_mail" title="E-mail the corresponding author ; Martin Rehaka ; b ; marrehak@cisco.com" class="auth_mail" title="E-mail the corresponding author
- 关键词：Network anomaly detection ; Regression smoothing ; False positive rate reduction
- 刊名：Journal of Computer and System Sciences
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：83
- 期：1
- 页码：43-57
- 全文大小：1963 K
文摘
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Using LAMS to improve the output of network anomaly detection systems.
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LAMS reduces the amount of structured and unstructured false positives.
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Improvement in AUC shown on various malicious activities and two different anomaly detection systems.