Adaptive machine learning‐based alarm reduction via edge computing for distributed intrusion detection systems

Summary To protect assets and resources from being hacked, intrusion detection systems are widely implemented in organizations around the world. However, false alarms are one challenging issue for such systems, which would significantly degrade the effectiveness of detection and greatly increase the...

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Veröffentlicht in:	Concurrency and computation Jg. 31; H. 19
Hauptverfasser:	Wang, Yu, Meng, Weizhi, Li, Wenjuan, Liu, Zhe, Liu, Yang, Xue, Hanxiao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hoboken Wiley Subscription Services, Inc 10.10.2019
Schlagworte:	Adaptive algorithms Artificial intelligence Cloud computing Delay distributed system Edge computing False alarms intelligent false alarm filter intrusion detection Intrusion detection systems Machine learning Reduction Response time System effectiveness Workload
ISSN:	1532-0626, 1532-0634
Online-Zugang:	Volltext
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