Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model

By Shadi A. Aljawarneh, Monther Aldwairi, M. B. Yassein. Journal of Computer Science, 2017

642 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/580d97167e33e000a5df963cd4a9b3a1f96397ef

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Fabio Antonelli
2. Massimo Vecchio
3. Mohammad Ali Jabraeil Jamali
4. Arash Heidari

In Computer Networks and Communications

1. Fabio Antonelli
2. Mojtaba Eskandari
3. Z. H. Janjua
4. Massimo Vecchio
5. Mohammad Ali Jabraeil Jamali
6. Arash Heidari

In Signal Processing

1. Fabio Antonelli
2. Massimo Vecchio
3. Mohammad Ali Jabraeil Jamali
4. Arash Heidari

Citations in the corpus

• Passban IDS: An Intelligent Anomaly-Based Intrusion Detection System for IoT Edge Devices (2020, result): “However, in this domain, this is a typical assumption, shared also with the recent state-of-the-art literature (see [15], [51]).”
• CICIDS-2017 Dataset Feature Analysis With Information Gain for Anomaly Detection (2020, background): “Researchers in [18] and in [21] use a score feature above 0.”