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Inicio  /  Applied Sciences  /  Vol: 10 Par: 8 (2020)  /  Artículo
ARTÍCULO
TITULO

Online Mining Intrusion Patterns from IDS Alerts

Kai Zhang    
Shoushan Luo    
Yang Xin    
Hongliang Zhu and Yuling Chen    

Resumen

In this paper, an influence model is proposed to tackle the sequence data analysis problems such as disordering, element missing and random noises. The proposed method can be used for mining intrusion patterns from the intrusion action sequence extracted from IDS (Intrusion Detection System) alerts.

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REVISTAS SIMILARES
Applied Sciences
Computers
Water

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