AUTOENCODER-BASED INTRUSION DETECTION IN CRITICAL INFRASTRUCTURES

Abstract

Securing critical infrastructure systems such as electricity, energy, health, management, transportation, and production facilities against cyber attacks is the issue on which states spend the most time and money when creating security strategies. Every day, different methods have emerged to prevent attackers who endanger our personal and national security with varying types of attacks. The most important of these methods is intrusion detection systems. This study proposes an autoencoder-based intrusion detection system model to detect security anomalies in critical infrastructures. The accuracy of this proposed model in attack detection has been tested with the current and complex UNSW-NB15 dataset. In the proposed model, training and testing steps were carried out using the attack packages in the data set. These packages are then divided into two: normal or attack. According to the results obtained in the experiments, it has been confirmed that the proposed intrusion detection system can effectively detect attacks with high performance.

Keywords

• Intrusion Detection System
• Critical Infrastructure
• Autoencoder

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