Publication

Abstract : The rise of the Internet of Things (IoT) has led to an increased risk of cyber attacks on IoT devices, including botnet attacks. Botnets are networks of compromised devices that can be controlled remotely by cybercriminals to carry out malicious activities, such as distributed denial of service (DDoS) attacks. The Mirai botnet is one of the most notorious botnets that have caused significant damage to IoT devices worldwide. To protect IoT devices from such attacks, intrusion detection systems (IDSs) are used to detect and mitigate attacks. However, the effectiveness of IDSs against botnet attacks is still a subject of debate, as botnets are becoming more sophisticated and difficult to detect. To address this issue, this research paper aims to analyse and compare the effectiveness of three widely used IDSs, namely Snort, Zeek, and Suricata, against the Mirai botnet. The study involves simulating Mirai botnet attacks in a controlled environment and evaluating the performance of each IDS in terms of detection and mitigation capabilities. The findings of this research can help organisations to select and implement effective IDSs to mitigate the impact of botnet attacks on IoT devices. By understanding the strengths and weaknesses of different IDSs, organisations can improve the security of their IoT devices and reduce the risk of cyber attacks. Overall, this research paper contributes to the existing literature on IDSs and their effectiveness against botnet attacks, highlighting the importance of selecting and implementing effective IDSs to protect IoT devices from cyber threats.