Journal of Cybersecurity and Information Management JCIM 2690-6775 2769-7851 10.54216/JCIM https://www.americaspg.com/journals/show/3031 2019 2019 Assistant professor, Department of Computational Intelligence, SRM Institute of Science and Technology, Kattankulathur-603203, Tamilnadu, India S. S. Assistant professor,Sri krishna college of Engineering and Technology, Coimbatore, India Kalaivani .N Assistant Professor (SG), Department of ECE, Nehru Institute of Engineering and Technology, Coimbatore, India Mohammedkasim .M Assistant Professor, Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam. Tamil Nadu, India D. Prabha .. Associate Professor, Department of CSE, Hindusthan Institute of Technology, Coimbatore, India E. Babu Thirumangaialwar A more extensive attack surface for cyber incursions has resulted from the fast expansion of Internet of Things (IoT) devices, calling for more stringent security protocols. This research introduces a new method for protecting Internet of Things (IoT) networks against intrusion assaults by combining Game Theory with Ant Colony Optimization (ACO). Various cyber dangers are becoming more common as a result of the networked nature and frequently inadequate security measures of IoT devices. Because these threats are ever-changing and intricate, traditional security measures can't keep up. An effective optimization method for allocating resources and pathfinding is provided by ACO, which takes its cues from the foraging behavior of ants, while Game Theory provides a strategic framework for modeling the interactions between attackers and defenders. Attackers and defenders in the proposed system are modeled as players in a game where the objective is to maximize their payout. Minimizing damage by anticipating and minimizing assaults is the defender's task. The monitoring pathways are optimized and resources are allocated effectively with the help of ACO. In response to changes in network conditions, the system dynamically modifies defensive tactics by updating the game model in real time. The results of the simulation show that the suggested method successfully increases the security of the Internet of Things. Compared to 87.4% using conventional approaches, the detection accuracy increased to 95.8%. From 10.5 seconds down to 7.3 seconds, the average reaction time to identified incursions was cut in half. Furthermore, there was a 20% improvement in resource utilization efficiency, guaranteeing that defensive and monitoring resources were allocated optimally. Internet of Things (IoT) network security is greatly improved by combining Game Theory with Ant Colony Optimization. In addition to enhancing detection accuracy and reaction times, this combination method guarantees resource efficiency. The results demonstrate the practicality of this approach, which offers a solid foundation for protecting Internet of Things devices from ever-changing cyber dangers. 2024 2024 275 286 10.54216/JCIM.140219 https://www.americaspg.com/articleinfo/2/show/3031