As a efficient way to cope with various attacks, the Random Forest(RF) algorithm has frequently been used as the core engine of intrusion detection because of ...
We evaluated the performance of the proposed algo- rithm in intrusion detection field by using a dataset which are mainly used for IDS performance evaluation: ...
In this paper, we provide a comparative study between twelve supervised machine learning methods. This comparative study aims to exhibit the best machine ...
Intrusion is described as a harmful act that compromises a computer system. The anomalies and IDS have become an important part of system defense as a result of ...
This paper proposes an effective deep learning method, namely AE-IDS (Auto-Encoder Intrusion Detection System) based on random forest algorithm.
Jun 23, 2021 · Intrusion Detection Systems are a useful technology for network administrators. The function of IDS is to recognize an anomalous behavior or an ...
It is an online-network-based IDS. It can detect known attacks as well as unknown attacks. ADAM uses association rules algorithm for intrusion detection. It ...
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Attack types and intrusion detection systems, and related works to the topic are discussed in this chapter. 2.1 Attack Types. In order to understand the reason ...
Nov 13, 2024 · Intrusion detection system tries to detect computer attacks by examining various data records, log audits etc. Many existing IDS such as Snort ...
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Oct 22, 2024 · The testing findings on the KDD CUP 1999 dataset for the proposed hybrid network intrusion detection system using IDS-RS showed 93.3% accuracy ...