Anomaly detection optimization using big data and deep learning to reduce false-positive

Anomaly detection optimization using big data and deep learning to reduce false-positive

Abstract Anomaly-based Intrusion Detection System (IDS) has been a hot research topic because of its ability to detect new threats rather than only memorized signatures threats of signature-based IDS. Especially after the availability of advanced technologies that increase the number of hacking tool...

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Bibliographic Details
Main Authors: Khloud Al Jallad, Mohamad Aljnidi, Mohammad Said Desouki
Format: Article
Language:English
Published: SpringerOpen 2020-08-01
Series:Journal of Big Data
Subjects:
Intrusion detection systems (IDS)
Security intelligence optimization
Unknown threats
Big data
NSL-KDD dataset
False-positive
Online Access:http://link.springer.com/article/10.1186/s40537-020-00346-1

Internet

http://link.springer.com/article/10.1186/s40537-020-00346-1

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