This paper presents a systematic literature review of IoT botnet DDoS attacks and evaluation of detection techniques. The review discusses the architecture of IoT botnet DDoS attacks, evaluations of these attacks, and systematically categorized detection techniques. The paper presents current threats and detection techniques, and recommends open research questions for future studies. The review focuses on the vulnerabilities inherent in IoT devices, assesses the effectiveness of current detection strategies, and identifies areas that need further research and development to strengthen IoT security against DDoS attacks. The paper also discusses the evolution of IoT botnets, including the Mirai botnet, and the various detection techniques used to identify and mitigate botnet DDoS attacks. The review covers host-based and network-based detection techniques, including SIEM-based, SDN-based, and DNS-based detection methods. The paper also discusses the use of machine learning and deep learning techniques for detecting botnet DDoS attacks. The review highlights the importance of improving IoT security measures to mitigate the risk of such cyberattacks. The paper concludes with a discussion of the contributions of this literature review to the field of IoT botnet DDoS attack detection and prevention.This paper presents a systematic literature review of IoT botnet DDoS attacks and evaluation of detection techniques. The review discusses the architecture of IoT botnet DDoS attacks, evaluations of these attacks, and systematically categorized detection techniques. The paper presents current threats and detection techniques, and recommends open research questions for future studies. The review focuses on the vulnerabilities inherent in IoT devices, assesses the effectiveness of current detection strategies, and identifies areas that need further research and development to strengthen IoT security against DDoS attacks. The paper also discusses the evolution of IoT botnets, including the Mirai botnet, and the various detection techniques used to identify and mitigate botnet DDoS attacks. The review covers host-based and network-based detection techniques, including SIEM-based, SDN-based, and DNS-based detection methods. The paper also discusses the use of machine learning and deep learning techniques for detecting botnet DDoS attacks. The review highlights the importance of improving IoT security measures to mitigate the risk of such cyberattacks. The paper concludes with a discussion of the contributions of this literature review to the field of IoT botnet DDoS attack detection and prevention.