Journal of Intelligent Systems and Internet of Things JISIoT 2690-6791 2769-786X 10.54216/JISIoT https://www.americaspg.com/journals/show/3605 2019 2019 Computer Department, College of Education for Pure Sciences, Wasit University, Iraq Oday Oday Computer Department, College of Education for Pure Sciences, Wasit University, Iraq; Ministry of Education, Wasit Education Directorate. Iraq Oday Ali Hassen College of Dentistry, Al-Iraqia University, Baghdad, Iraq Wisam Makki Salim National Advanced IPv6 Centre (NAv6), Universiti Sains Malaysia, Gelugor 11800, Penang, Malaysia Selvakumar Manickam Department of Information Technology, University Technical Malaysia Melaka, Hang Taya, Melaka 76100, Malaysia Nur Azman Abu Wireless sensor networks have become a vital component of the infrastructure for many modern applications. With the increasing use of wireless sensor networks, the challenges facing these networks in the field of security are escalating and growing, and with the rapid advancement of wireless communication technology, these networks are exposed to increasing, complex and continuous threats. Our research is characterized by innovation in the field of security technology to enhance protection, repel attacks and detect intrusions, among these innovations are intrusion detection systems based on machine learning as a creative and new solution. In this research, we highlight the effectiveness of different machine learning algorithms, such as supervised and unsupervised learning, in detecting anomalies and intrusions within wireless sensor networks, as our goal focuses on enhancing the security of wireless sensor networks (WSNs) by adopting intrusion detection systems (IDS) based on machine learning techniques. In this context, with a focus on using the WSN-DS dataset. The results of this research showed that machine-learning models could improve the security efficiency of wireless sensor networks by achieving accuracy ranging from 91% to 99.7% and testing time ranging from 0.006 to 0.1249, which enhances the ability to effectively retrieve and detect threats in real time. 2025 2025 176 188 10.54216/JISIoT.160115 https://www.americaspg.com/articleinfo/18/show/3605