Comparison of feature extraction tools for network traffic data

TL;DR

This paper compares popular feature extraction tools for network traffic data, emphasizing their importance in enhancing AI-based intrusion detection systems' efficiency and accuracy.

Contribution

It provides a comparative analysis of feature extraction tools, highlighting their impact on AI-IDS performance and guiding tool selection for better security outcomes.

Findings

Identifies key differences among feature extraction tools

Shows how tool choice affects IDS accuracy

Provides recommendations for tool selection

Abstract

The comparison analysis of the most popular tools to extract features from network traffic is conducted in this paper. Feature extraction plays a crucial role in Intrusion Detection Systems (IDS) because it helps to transform huge raw network data into meaningful and manageable features for analysis and detection of malicious activities. The good choice of feature extraction tool is an essential step in construction of Artificial Intelligence-based Intrusion Detection Systems (AI-IDS), which can help to enhance the efficiency, accuracy, and scalability of such systems.