![]() ![]() Then, the performance of IDS was evaluated in terms of G-mean and Area Under Curve (AUC). The MSCAD was assessed in two manners firstly, the MSCAD was used to train IDS. MSCAD includes two multi-step scenarios the first scenario is a password cracking attack, and the second attack scenario is a volume-based Distributed Denial of Service (DDoS) attack. In this work, a new benchmark Multi-Step Cyber-Attack Dataset (MSCAD) is introduced. ![]() However, implementing a robust IDS needs a reliable and up-to-date dataset in order to capture the behaviors of the new types of attacks, especially multi-step attacks. Thus, the need for a reliable and acceptable Intrusion Detection System (IDS) solution is becoming urgent to protect the networks and devices. Nowadays, with the rapid increase in the number of applications and networks, the number of cyber multi-step attacks has been increasing exponentially. ![]()
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